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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Snowflake Postgres team is building a managed Postgres experience inside Snowflake. This role is focused on the control plane, where you have the opportunity to work on both on distributed systems at scale and also to work on research grade optimizations at various layers of the software stack including but not limited to provisioning, managing, securing, and operating Postgres in Snowflake . You will work on core backend systems that sit at the intersection of distributed systems, database infrastructure, security, and operational excellence. In this role, you will: Design and build backend services that power provisioning, lifecycle management, and configuration of Snowflake Postgres instances. Develop features in the access and user model, including authorization, secure administration flows, and customer-facing management capabilities. Improve the reliability, observability, and operability of asynchronous workflows and background systems that keep the service healthy. Partner with product, security, and adjacent engineering teams to deliver simple customer experiences on top of complex infrastructure. Investigate production issues, participate in on-call, and drive fixes that improve resilience and reduce operational burden. Contribute to technical design, code review, and mentoring while helping raise the engineering bar across the team. Our ideal candidate will have: 2+ years of experience building production software in backend, infrastructure, or distributed systems environments. Strong programming skills in one or more of Java, Go, C++, or Python. Strong computer science fundamentals, including concurrency, networking, APIs, and data structures. Experience designing and operating reliable services in production, including debugging, monitoring, and incident response. Experience working across technical boundaries with product, security, and other engineering teams. BS/MS in Computer Science, Engineering, or a related field, or equivalent practical experience. Nice to have: Experience with PostgreSQL, database internals, or managed database platforms. Experience with identity, authorization, RBAC, or other security-sensitive systems. Experience with cloud infrastructure on AWS, Azure, or GCP. Experience with workflow orchestration, control plane systems, or highly asynchronous service architectures. Why join this team? Work on a strategic product area that expands Snowflake into transactional and operational database workloads Build systems that directly shape how customers create, manage, and secure Postgres inside Snowflake Tackle a mix of product engineering, infrastructure, reliability, and security problems. Join a collaborative team with meaningful ownership, strong technical challenges, and room to grow Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Build the Future of Data. Join the Snowflake Team. We are actively hiring software engineers from Europe and around the world for our European Engineering Center. Our office is located at Potsdamer Platz, in the heart of Berlin. It’s easily accessible by train, subway, bus, or bicycle – with numerous restaurants, cafes, and shops within walking distance. The official language for this office is English. This is a fantastic opportunity to join a team of skilled engineers, building and maintaining the future of the Java infrastructure that powers the data cloud. As part of this team, you will work on the core Java libraries and JVM infrastructure that support our scalable, high-performance platform, impacting millions of users globally. AS A SOFTWARE ENGINEER ON THE JAVA PLATFORM TEAM, YOU WILL: Contribute to building the next-generation systems that make using Java safe, efficient, and secure Help provide a consistent, high-performance platform that Snowflake engineers can use to deliver high-quality solutions to production. Identify performance and availability issues, implement effective solutions, and instrument key components as needed. Collaborate with global teams to solve real-world, large-scale challenges in data infrastructure. Continuously improve the reliability and performance of our Java infrastructure through proactive monitoring and automation. WE ARE LOOKING FOR SOFTWARE ENGINEERS WHO: Have experience building, supporting, and troubleshooting complex Java systems. Understand Java fundamentals, including the JVM and core libraries. Have solid computer science fundamentals, including data structures, algorithms, and distributed systems. Are eager to learn about JVM internals and performance tuning. Thrive in collaborative environments, contributing to shared team goals. Have a BS in Computer Science or equivalent experience (advanced degrees a plus). Bonus points for: Experience with multi-threading, concurrency, and caching. Knowledge of database or Linux internals. Previous experience with large-scale, high-performance systems. Join us and be a part of a team that is driving the future of the data cloud. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Staff Software Engineer for our Frontier Security AI team. Snowflake's Frontier Security AI teams develop production-grade LLM applications, intelligent agents, AI infrastructure, and evaluation systems for enterprise customers — products that must meet a high bar for quality, security, reliability, and efficiency while operating over sensitive data at large scale. In this role, you will lead the design and development of our Agentic Harness and agent evaluation platform, working across product, infrastructure, applied AI, security, and modeling teams to take new capabilities from prototype to dependable customer value. AS A STAFF SOFTWARE ENGINEER AT SNOWFLAKE, YOU WILL: Architect and build the Agentic Harness that executes complex, multi-step AI workflows across models, tools, data, and services. Design stable interfaces for tool execution, context construction, state management, memory, permissions, retries, fallbacks, and human review. Own agent quality end to end by building evaluation harnesses, representative datasets, automated graders, experiment pipelines, and release gates. Convert ambiguous reports such as "the agent feels worse" into measurable failure modes, reproducible tests, and durable fixes. Analyze production agent trajectories to identify failures in reasoning, retrieval, tool use, context, orchestration, and application code. Close the loop between production incidents, root-cause analysis, evaluation coverage, and regression prevention. Develop offline and online measurements for task completion, correctness, groundedness, safety, latency, reliability, and cost. Build simulation and replay infrastructure for golden-set tests, adversarial scenarios, model comparisons, and large-scale experiments. Improve agent efficiency through model routing, prompt and semantic caching, context compaction, tool-result management, and token optimization. Productionize new model capabilities as secure, observable, multi-tenant services with clear operational controls. Establish standards for evaluation design, including sampling, ground-truth quality, grader calibration, leakage prevention, and statistical significance. Define technical direction across multiple teams and lead projects whose scope extends beyond a single service. Mentor engineers, raise the quality of architecture reviews, and remain directly involved in implementation and debugging. OUR IDEAL STAFF SOFTWARE ENGINEER WILL HAVE: 9+ years of software engineering experience, including technical leadership of complex production systems. Direct experience shipping and operating LLM applications, AI agents, or model-backed workflows in production. Strong background in distributed systems, service architecture, high-throughput APIs, concurrency, and failure handling. Experience building an agent runtime, workflow engine, developer platform, evaluation system, or similar infrastructure. Demonstrated ability to evaluate nondeterministic systems without relying on a single aggregate score. Fluency in Python and strong proficiency in at least one systems or application language such as Java, Go, Rust, or TypeScript. Hands-on knowledge of tool calling, structured generation, retrieval, context engineering, prompt management, and model APIs. Experience with production observability, including structured traces, replay, metrics, logs, and incident diagnosis. Ability to balance agent quality with latency, reliability, security, and inference cost. Track record of setting technical direction and delivering results across organizational boundaries. Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Clear written and verbal communication with engineering, product, and leadership audiences. BONUS POINTS FOR THE FOLLOWING: Building evaluation or observability infrastructure for agentic coding, data engineering, or analytics systems. Designing human-evaluation programs, scoring rubrics, annotation workflows, or grader-calibration methods. Working with multi-agent orchestration, long-running agents, asynchronous workflows, or durable execution. Developing synthetic tasks, simulations, adversarial tests, red-team exercises, or safety guardrails. Building retrieval systems that use vector search, hybrid search, semantic indexing, ranking, or caching. Operating multi-tenant systems that process sensitive enterprise data. Working with model training, fine-tuning, reinforcement learning, or feedback-driven optimization. Evaluating and onboarding frontier models based on measured product outcomes. Experience with databases, SQL engines, data platforms, Kubernetes, or cloud-native infrastructure. YOU MAY BE A PARTICULARLY GOOD FIT IF YOU: Treat evaluation as part of product engineering rather than a final validation step. Can move between agent behavior, distributed infrastructure, data analysis, and production debugging. Question metrics that do not reconcile and design tests that can expose misleading results. Take ownership from early architecture through deployment, operations, and measurable customer outcomes. Prefer evidence from representative tasks and production behavior over isolated benchmark results. Work effectively in fast-moving environments where requirements develop through experimentation. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Job Location: 135 Constitution Drive, Menlo Park, CA 94025. ELT: Engineering REQ ID: ASHREQ-8246 Joining this team means architecting the performance, scalability, and service infrastructure that will empower the world's largest enterprises to seamlessly govern their transactional and analytical data in one place. If you are passionate about building industry-leading technologies that solve real-world scale and performance problems, this is the place to be. In this role, you will be a key contributor to the evolution of our core product: an elastic, large-scale, high-performance data processing system. We are looking for smart, enthusiastic engineers who can quickly master complex technical areas and are passionate about building new, industry-leading technologies. AS A SENIOR SOFTWARE ENGINEER (MULTIPLE POSITIONS AVAILABLE) AT SNOWFLAKE, YOU WILL: Design, develop, and maintain core components of AI/ML observability systems, including backend infrastructure for largescale data processing, storage, and data movement. Implement and optimize highly specialized techniques such as sketch based data aggregation and machine learning metrics to support accurate monitoring and evaluation of ML and Generative AI models. Develop and enhance AI/ML infrastructure to support reliable training, deployment, and monitoring of machine learning workloads at scale. Build and extend platform features that enable scalable ML and Generative AI use cases while improving performance, reliability, and resource efficiency. Serve as a technical lead for the design and implementation of machine learning observability, data infrastructure, and model explainability capabilities supporting customer-facing ML and Generative AI products. Telecommuting permitted. Minimum Requirements for Position: Bachelor's degree or foreign equivalent in Computer Science, Information Technology, Electrical Engineering or a related field, and five (5) years of progressive post baccalaureate experience in the job offered or a related occupation. Education or experience must include: Designing and building database systems, compilers, and developer tools; Building enterprise-grade, reliable, and trustworthy software and services; Developing applications using Java; Using SQL and other database technologies, including implementing internal database components; Designing data warehouses, database systems, and large-scale data processing solutions; Contributing to ASF open-source projects, including big data and Hadoop ecosystem initiatives; and Performing implementation, testing, debugging, and documentation, and design query compilation and compiler systems. The base salary range for this role is $221,187 - $287,500 Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. As a Senior/Staff Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on technical leader and trusted partner to our most strategic customers. You will own the end-to-end delivery of enterprise AI programs, leading a team of 2–4 engineers while staying deeply technical yourself . You will set the technical direction for your customer engagements, mentor your team, and serve as the senior technical voice at the intersection of product, engineering, and customer success. Note: This is a customer facing role & require frequent travelling within USA mostly IN THIS ROLE AT SNOWFLAKE, YOU WILL: Lead Customer Programs : Own the full lifecycle of complex, multi-engineer AI engagements – from scoping and architecture through deployment, monitoring, and handoff. Be accountable for delivery quality and customer outcomes for the projects you lead. Own AI Quality : Define what "good" means for each engagement. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Set the standard for how the team measures and improves AI systems in production. Grow and Mentor Engineers : Provide day-to-day technical leadership and mentorship to a team of 2–6 Applied AI Engineers. Review designs and code, unblock teammates, and actively develop their skills and careers. Deliver with Velocity : Remain a hands-on contributor – designing, iterating, and shipping high-quality ML pipelines and agentic AI solutions alongside your team. Translate ambiguous business objectives into robust, scalable, and performant solutions. Productionize AI at Scale : Own the full implementation lifecycle for AI solutions, from prototype through deployment, monitoring, and optimization in secure, large-scale production environments. Build the safety guardrails, observability, and human-review workflows that keep AI applications reliable and trustworthy – and close the loop from production traces and user feedback back into your evals so quality compounds over time. Be a Strategic Technical Advisor : Serve as a senior technical advisor to customer data science and engineering leadership. Set the standard for how Snowflake AI is deployed and articulate complex technical concepts to both technical and executive stakeholders. Collaborate to Innovate : Work cross-functionally with Snowflake's Product and Engineering teams, bringing real-world patterns and feedback from the field to directly shape the future of Snowflake's AI platform. Drive Compounding Outcomes : Identify recurring deployment patterns and turn them into reusable assets – reference architectures, evaluation harnesses, and product feedback that scale Snowflake's impact across customers. Have the opportunity to travel : Spend at least 25% of your time onsite, working closely with Snowflake's most strategic customers. WE'RE LOOKING FOR CANDIDATES WHO HAVE: Demonstrated experience leading technical projects or teams, including setting technical direction, reviewing others' work, and driving delivery to completion. Proven experience building and productionizing applications using LLMs, especially with technologies like RAG and agentic workflows. Hands-on experience defining quality metrics and evaluation frameworks for LLM or agent systems, and using evals to systematically improve quality over time. Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to both technical and executive stakeholders. Comfort with ambiguity and the ability to independently structure and execute on complex, open-ended problems. 7+ years of professional software engineering experience. Experience in a customer-facing technical role. Willingness to travel. Preferred Qualifications Experience building eval sets from production traces and synthetic data, and running structured experimentation (A/B tests, ablations, offline evals) to compare prompts, models, or agent architectures. Familiarity with eval and observability tooling (e.g., Braintrust, LangSmith, Arize, Weave, Promptfoo) or experience building custom eval harnesses. Experience with failure-mode analysis on agent or RAG systems – categorizing errors (hallucination, retrieval miss, planning failure, tool misuse) and driving each down with targeted evals. Hands-on experience with the MLOps lifecycle, including model deployment, monitoring, and evaluation in a cloud environment (AWS, Azure, or GCP). Familiarity with core data science libraries and tools (e.g., pandas, numpy, Snowpark). Startup experience or experience in a high-growth, fast-paced environment. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee’s duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Principal Software Engineer - Agentic Pipelines Building for AI-Enabled Data Engineers & Scientists Data pipelines are foundational infrastructure — when they're fast, correct, and maintainable, customers build on them with confidence. If you've spent the bulk of your career building large-scale data infrastructure — designing streaming or transformation primitives, reasoning hard about consistency and fault tolerance, and owning the systems that run under millions of customer workloads — this role might be for you. You'll be working on the pipeline layer at Snowflake: the constructs that define how customers move, shape, and maintain data. AI has a real presence in this work — in how customers use these pipelines and in how we think about building them — but the core job is hard data/pipeline infrastructure engineering, and that's what we're hiring for. About the Team We build the core data engineering primitives that power Snowflake's streaming and transformation capabilities. From the constructs customers use to define real-time pipelines to the execution fabric that makes those pipelines reliable and cost-efficient at cloud scale, our team owns the full stack of declarative data engineering. We're a small, high-ownership team operating close to the product — which means your decisions ship, your architecture matters, and your fingerprints are on some of the most heavily used features in Snowflake's data engineering portfolio. What You'll Do Define and drive the technical direction for Snowflake's core data engineering and streaming transformation primitives, spanning Streams, Tasks, Dynamic Tables, and adjacent pipeline constructs. Identify and lead multi-quarter technical investments — performance, scalability, correctness, and reliability — translating ambiguous problem spaces into concrete engineering plans with measurable outcomes. Partner with product, research, and peer engineering teams to co-design primitives that compose cleanly across the data engineering stack. Operate as a force multiplier: run architectural reviews, set the technical bar for design documents, and help engineers grow through high-quality feedback and sponsorship. Work directly with customers and field teams to understand real-world usage patterns; use that signal to prioritize what matters next. Contribute to Snowflake's technical reputation — through internal design influence, external talks, or research publications in the data engineering space. What We're Looking For 15+ years of experience designing, building, and operating large-scale distributed data systems. Deep expertise in at least one core area: stream processing, declarative query execution, pipeline orchestration, or data transformation at scale. Strong computer science fundamentals — distributed systems, algorithms, fault tolerance, and consistency models. Proficiency in C++ or Java; comfort with systems-level reasoning (latency, throughput, resource efficiency at cloud scale). Demonstrated ability to lead cross-team technical initiatives from blank-page architecture through production at petabyte scale across thousands of concurrent workloads. Strong written and verbal communication skills; ability to represent complex technical trade-offs clearly to engineering, product, and leadership audiences. Nice to Have Experience with one or more major analytical databases (Snowflake, BigQuery, Redshift, Databricks, Teradata, etc). Hands-on background in streaming, transformation, or event-driven systems (Flink, Kafka, Spark Structured Streaming). Familiarity with the broader data engineering ecosystem: dbt, Airflow, Fivetran, Iceberg, Delta Lake. Experience with CDC, change propagation, or incremental computation patterns. Advanced degree (MS or PhD) in Computer Science, with emphasis on database or distributed systems. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Cortex Apps team is building the future of AI for enterprise data. This role focuses on the backend infrastructure that powers our flagship products like Snowflake Intelligence , Cortex Agents and Search making agentic AI fast, reliable, scalable and secure at the enterprise level. You won’t just be using AI tools; you will be building the high-performance systems that orchestrate them. You’ll own and influence the architecture for agent execution environments, high-throughput context retrieval, or the ecosystem that allows our customers to iterate and launch agents in production. What you will do in this role: Architect Agentic Runtimes: Build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management. Scale Context Engineering Infra: Design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable and efficient search indexing, query processing, and result ranking, semantic caching, and automated metadata extraction. Build the "Evals Engine": Develop the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and "hillclimbing" experiments. Productionize AI Workflows: Collaborate with the modeling team to take raw LLM capabilities and turn them into hardened, multi-tenant microservices with strict guardrails and observability. Optimize Performance & Cost: Direct the infra strategy for model routing, prompt caching, and token optimization to ensure Snowflake’s AI features are the most efficient in the industry. Requirements: Education: Bachelor’s degree in Computer Science or a related technical field. Experience: 7+ years of experience building distributed systems , high-throughput APIs, or backend infrastructure for AI/ML products. Technical Stack: Deep proficiency in Go or Java (for systems) and Python (for AI orchestration). Systems Thinking: Strong understanding of database internals, distributed state management, and cloud-native architecture (Kubernetes, FoundationDB, etc.). Domain Expertise: Familiarity with the "plumbing" of AI: vector indices, agent platforms, and building scalable data pipelines. Experience in a customer-facing technical role — you have explained a hard failure to a frustrated external audience and been believed, you can produce both the internal analysis and the customer-safe version. Product instinct — you can judge whether one customer's problem is bespoke or a platform gap worth fixing for everyone. This is the core judgment call. Cross-layer debugging — tracing a request across services and root-causing in unfamiliar code from logs and telemetry, not guesswork. Eval frameworks for LLM/agent systems — defining quality metrics and using evals to improve quality systematically over time. Comfort with ambiguity on open-ended, externally-driven problems. (Bonus) Experience with: Query optimization and SQL engine internals. Designing multi-tenant systems that handle sensitive enterprise data at scale. Developing search infrastructure for large-scale applications. Direct experience with any of the subsystems outlined above. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. There is only one Data Cloud. Snowflake’s founders started from scratch and designed a data platform built for the cloud that is effective, affordable, and accessible to all data users. But it didn’t stop there. They engineered Snowflake to power the Data Cloud, where thousands of organizations unlock the value of their data with near-unlimited scale, concurrency, and performance. This is our vision: a world with endless insights to tackle the challenges and opportunities of today and reveal the possibilities of tomorrow. FoundationDB (FDB) is an open source, highly scalable database capable of ACID transactions at high frequencies and low latencies. FDB has been a core component in Snowflake's unique shared-metadata architecture since 2014, making possible Snowflake's vision to build the greatest data warehouse for the cloud. FDB performs millions of transactions per second across thousands of processes. The FDB team builds features on open-source FDB that improve the performance, scale, reliability and operability of the product. We are looking for an outstanding Senior Software Engineer with a passion for large scale databases and distributed systems to help us take FoundationDB to the next level. FoundationDB powers all of Snowflake’s products and services and is rapidly evolving to meet Snowflake’s future needs. We are growing at a fast rate and we need to scale FoundationDB by at least one order of magnitude over the next few years. Additionally, new workloads are emerging that need FoundationDB’s reliability, high availability and strong consistency semantics. These workloads will require innovation to re-architect the core components of our system. AS A SENIOR SOFTWARE ENGINEER AT SNOWFLAKE, YOU WILL: Identify strategically important problems, inefficiencies or opportunities for impactful improvements Own the end to end delivery of your projects, from identifying a solution, to design, implementation, test and safe production rollout Design and implement critical high performance systems to handle the ever growing request rate of our database Build the next generation transaction system, caching, storage engine and multi tenant capabilities Evangelize best practices in database usage and end-to-end architecture. Analyze and understand performance and scalability bottlenecks in the system and solve them. Pinpoint problems, instrument relevant components as needed, and ultimately implement solutions. OUR IDEAL SENIOR SOFTWARE ENGINEER WILL HAVE: 6+ years hands-on software engineering experience. Systems programming skills including multi-threading, concurrency, etc. Fluency in C++, C, or Java is preferred. Experience designing, building, and operating large-scale distributed systems or web services Experience with scalable Key-Value stores such as FoundationDB, RocksDB/LevelDB, DynamoDB, Redis, etc. a plus. Strong CS fundamentals including data structures, algorithms, and distributed systems. Track record of delivering highly complex projects in the distributed systems space Intense curiosity, willingness to question and passion for making systems better Strong technical problem solving, communication, and collaboration skills Excitement by the challenge of hard technical problems BS in Computer Science; Masters or PhD Preferred. About Snowflake: Snowflake SIGMOD 2016 paper About FoundationDB: FDB SIGMOD 21 Paper FoundationDB Summit 2018 and FoundationDB Summit 2019 How FDB powers Snowflake Metadata Forward! Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com