Careers at Geniusai

About Genius AI Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more. Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points. About the Role As we continue to expand our reach and impact, we are seeking highly motivated and talented engineering interns to join our team for Winter of 2027. Position: Engineering Intern Location: NYC Duration: January 19, 2027 – April 30, 2027 This internship puts you inside a live engineering team shipping product that hundreds of thousands of service businesses and their clients touch every day. You'll work on real features headed to production, not a side project built to keep you busy. Genius AI is scaling an agentic product at a pace where decisions ship in days, and this role exists so you get real exposure to how that speed and judgment work together. You will report to an engineering manager on our team. You must be commutable to our NYC headquarters in Union Square, and will operate in an in-person environment. We default to being in-office 3-4 days per week with required attendance on Tuesdays and Thursdays. What You'll Do Build and test features for our web and mobile products alongside senior engineers, shaping experiences used by our customers and their clients Architect small pieces of automation with AI, not just use it as an assistant: identify repeatable work in your own project and build the system that removes it Write clean, efficient code that meets Genius AI engineering standards, and own debugging and troubleshooting Partner with data analysts to collect and interpret usage data, and use those insights to inform how AI gets applied across the product Ship fast, learn faster: iterate on your projects with AI-assisted development on a tight cadence, adjusting based on feedback from senior engineers Expand your technical range deliberately, picking up new languages, frameworks, and AI-native development practices as the team's needs shift What We're Looking For Currently pursuing a B.S. in Computer Science or related technical field, graduating between 2027 and 2028, with coursework or project experience in software engineering You use AI to learn faster, debug, and ship, and can point to something you've built with it You dig into a problem before waiting for someone to hand you the answer, and you ask for help once you're stuck, not before you've tried Proficient in one or more of JavaScript, TypeScript, Ruby, or Kotlin, with real project experience beyond coursework Comfortable picking up new frameworks and tools quickly, ideally with some exposure to React, Postgres, SQL, or gRPC Strong problem-solving instincts and equally comfortable working independently or pairing with a teammate Clear, direct communicator who can explain technical tradeoffs to both engineers and non-engineers Available to work in person from our Union Square, NYC office At Genius AI, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. We believe this benefits not only our employees but our product, customers, and community as well. Genius AI is proud to be an Equal Opportunity and Affirmative Action Employer. Personal Information: Notice at Collection for Employees and Applicants Agency Submissions If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired. Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.

About Genius AI Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more. Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points. About the role AI isn’t a strategic initiative for us; it’s how we work. Our bar is transformation, not adoption. The Applied AI team is an internal accelerator: a small pod of forward-deployed builders who find the work where AI changes the outcome, build it with the team that owns that work, and hand it off once it runs. We work on three fronts: Across the business (our primary focus). We embed with areas such as Sales, Marketing and Operations to rebuild how they work. We've shipped an outbound engine our GTM team runs on, and a paid-social insights platform with an embedded agent. The agent helped marketing find inefficient campaign spend that had been hiding in the data and the creative. Next up is the top of our funnel: taking an agentic approach to helping sales and marketing learn which messages, creative and channels actually work. At the frontier. New models, open-weight alternatives, generative UI and agent platforms, tested against real work, so we know what's possible before we need it. You will be the team's first engineering manager, and a builder first. Expect a real share of your week to be hands on: prototyping, pairing on agent architecture and evals, and building the thing yourself when that's the fastest way to make the point. You must be commutable to our NYC headquarters or San Francisco office. We default to being in-office 3–4 days per week, with required attendance on Tuesdays and Thursdays. What you'll do Build, and lead builders. Manage and grow a lean team of engineers, and set the bar for what a fully AI-native engineering team looks like. Drive measurable go-to-market outcomes (pipeline, demos, and closed-won revenue). Partnering across Engineering, Sales, Marketing, Finance, Legal, and People to ruthlessly prioritize a company-aligned backlog—anchoring every initiative to pre-agreed metrics and executive-trusted readouts. Run a tight engagement loop. Intake, one-week sprints with Friday demos, and a clean handoff at the end: a partner team that owns what was built, and a durable owner so Applied AI stays on the next problem instead of carrying the pager. Make evals a practice. Help drive us toward best-in-class here, and share learnings so that every AI product team has a measurable quality bar that lets them move fast safely. Route to the right model. Frontier models first for new use cases; cheaper or open-weight models once a use case is mature and well understood. Push the ways of working forward. Partner with DevEx on experiments that change how engineering works, and turn the ones that work into shared standards, docs and talks, so the whole company gets better at working with AI. What we're looking for You've personally built and shipped agentic systems with real users in the last 12 months. Not evaluated or piloted: shipped. Be ready to walk us through one (or a side project): the architecture, what failed, what it cost, and how you knew it worked. You can tell us how you'd measureAI effectiveness. "Everyone has a license" isn't an answer. We want your opinion on the metric, and on what it would get wrong. You'd rather grow output than headcount. You've changed how you and your engineers work because of AI, and raised your expectations of the team to match. You've managed engineers and still build. 7+ years of software engineering, including 2+ years managing, on a team small enough that you stayed in the code. A scrappy generalist with cross-functional instincts. You've sat inside a sales, marketing or operations team's workflow, understood it, and helped them adopt something new. You tie engineering work to business outcomes like pipeline, revenue, time saved or cost avoided, and report on them clearly. You're comfortable building the process where there isn't one, and only as much process as the team needs. At Genius AI, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. We believe this benefits not only our employees but our product, customers, and community as well. Genius AI is proud to be an Equal Opportunity and Affirmative Action Employer. Personal Information: Notice at Collection for Employees and Applicants Agency Submissions If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired. Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.

About Genius AI Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more. Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points. About the role AI isn’t a strategic initiative for us; it’s how we work. Our bar is transformation, not adoption. The Applied AI team is an internal accelerator: a small pod of forward-deployed builders who find the work where AI changes the outcome, build it with the team that owns that work, and hand it off once it runs. We work on three fronts: Across the business (our primary focus). We embed with areas such as Sales, Marketing and Operations to rebuild how they work. We've shipped an outbound engine our GTM team runs on, and a paid-social insights platform with an embedded agent. The agent helped marketing find inefficient campaign spend that had been hiding in the data and the creative. Next up is the top of our funnel: taking an agentic approach to helping sales and marketing learn which messages, creative and channels actually work. At the frontier. New models, open-weight alternatives, generative UI and agent platforms, tested against real work, so we know what's possible before we need it. You will be the team's first engineering manager, and a builder first. Expect a real share of your week to be hands on: prototyping, pairing on agent architecture and evals, and building the thing yourself when that's the fastest way to make the point. You must be commutable to our NYC headquarters or San Francisco office. We default to being in-office 3–4 days per week, with required attendance on Tuesdays and Thursdays. What you'll do Build, and lead builders. Manage and grow a lean team of engineers, and set the bar for what a fully AI-native engineering team looks like. Drive measurable go-to-market outcomes (pipeline, demos, and closed-won revenue). Partnering across Engineering, Sales, Marketing, Finance, Legal, and People to ruthlessly prioritize a company-aligned backlog—anchoring every initiative to pre-agreed metrics and executive-trusted readouts. Run a tight engagement loop. Intake, one-week sprints with Friday demos, and a clean handoff at the end: a partner team that owns what was built, and a durable owner so Applied AI stays on the next problem instead of carrying the pager. Make evals a practice. Help drive us toward best-in-class here, and share learnings so that every AI product team has a measurable quality bar that lets them move fast safely. Route to the right model. Frontier models first for new use cases; cheaper or open-weight models once a use case is mature and well understood. Push the ways of working forward. Partner with DevEx on experiments that change how engineering works, and turn the ones that work into shared standards, docs and talks, so the whole company gets better at working with AI. What we're looking for You've personally built and shipped agentic systems with real users in the last 12 months. Not evaluated or piloted: shipped. Be ready to walk us through one (or a side project): the architecture, what failed, what it cost, and how you knew it worked. You can tell us how you'd measureAI effectiveness. "Everyone has a license" isn't an answer. We want your opinion on the metric, and on what it would get wrong. You'd rather grow output than headcount. You've changed how you and your engineers work because of AI, and raised your expectations of the team to match. You've managed engineers and still build. 7+ years of software engineering, including 2+ years managing, on a team small enough that you stayed in the code. A scrappy generalist with cross-functional instincts. You've sat inside a sales, marketing or operations team's workflow, understood it, and helped them adopt something new. You tie engineering work to business outcomes like pipeline, revenue, time saved or cost avoided, and report on them clearly. You're comfortable building the process where there isn't one, and only as much process as the team needs. At Genius AI, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. We believe this benefits not only our employees but our product, customers, and community as well. Genius AI is proud to be an Equal Opportunity and Affirmative Action Employer. Personal Information: Notice at Collection for Employees and Applicants Agency Submissions If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired. Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.

About Genius AI Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more. Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points. About the Role We have committed to a software factory model: a standardized, automated, fault-tolerant path from an idea to production, where humans and AI agents both ship code every day. As our Staff Infrastructure Engineer, you'll be one of the main people designing and building that factory. That covers how we build, verify, deploy and operate software, and how AI accelerates each of those steps. It also includes our own internal agentic SRE product that the rest of engineering leans on. This is a hands-on, staff-level IC role on our Infrastructure team. You will treat CI pipelines, deploy tooling and alerting as products, with the rest of engineering as your customers, and you will judge the work by how much faster and safer every team ships. You will report to our VP of Engineering. You must be commutable to our San Francisco office and will operate in an in-person environment. We default to being in-office 3-4 days per week with required attendance on Tuesdays and Thursdays. What You'll Do Scale our CI platform as our orchestration layer for our software factory. Build systems that let engineers stop worrying about deploys Design the guardrails, validation and auto-approval paths that let product engineers change their own infrastructure as code safely, without waiting for an Infra reviewer Shape the tools, skills and breakglass access that let engineers and AI agents investigate and resolve incidents across the app, service, compute, storage and network layers, without someone from Infra on the call Own SLOs, codify monitoring in Terraform (no more ClickOps), and get rid of noisy or muted-forever monitors across the org Write technical designs, review the hard changes and mentor engineers around you. Your judgment will set the direction of the platform for the next few years What We're Looking For 8+ years of professional software engineering experience, including several years focused on infrastructure, platform or developer experience. A track record of staff-level ownership: you've set the technical direction for a platform or build/deploy system that many engineers depend on, and you can point to measurable gains in velocity or reliability. Deep hands-on experience with a major public cloud (AWS preferred) and operating Kubernetes in production. Fluency with infrastructure as code (Terraform) and GitOps-style delivery (ArgoCD or similar). Real experience designing CI/CD at scale: pipeline standardization, self-hosted runners, build caching, progressive delivery and safe rollbacks. Strong observability and reliability instincts. You've defined SLOs, cleaned up alerting, and turned incident follow-ups into fixes in the system rather than tickets that age out. A product mindset toward internal tooling. You measure success by adoption and by how rarely people need to ask Infra for help. AI tooling built into your development workflow in a meaningful way. You aren't just aware of the tools; you've changed how you work because of them, and you have opinions on how agents should fit into build, deploy and operations. Experience at a high-growth startup or a small, high-leverage platform team where you shipped quickly and worked through ambiguity without heavy process. At Genius AI, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. We believe this benefits not only our employees but our product, customers, and community as well. Genius AI is proud to be an Equal Opportunity and Affirmative Action Employer. Personal Information: Notice at Collection for Employees and Applicants Agency Submissions If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired. Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.

About Genius AI Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more. Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points. About the Role We have committed to a software factory model: a standardized, automated, fault-tolerant path from an idea to production, where humans and AI agents both ship code every day. As our Staff Infrastructure Engineer, you'll be one of the main people designing and building that factory. That covers how we build, verify, deploy and operate software, and how AI accelerates each of those steps. It also includes our own internal agentic SRE product that the rest of engineering leans on. This is a hands-on, staff-level IC role on our Infrastructure team. You will treat CI pipelines, deploy tooling and alerting as products, with the rest of engineering as your customers, and you will judge the work by how much faster and safer every team ships. You will report to our VP of Engineering. You must be commutable to our San Francisco office and will operate in an in-person environment. We default to being in-office 3-4 days per week with required attendance on Tuesdays and Thursdays. What You'll Do Scale our CI platform as our orchestration layer for our software factory. Build systems that let engineers stop worrying about deploys Design the guardrails, validation and auto-approval paths that let product engineers change their own infrastructure as code safely, without waiting for an Infra reviewer Shape the tools, skills and breakglass access that let engineers and AI agents investigate and resolve incidents across the app, service, compute, storage and network layers, without someone from Infra on the call Own SLOs, codify monitoring in Terraform (no more ClickOps), and get rid of noisy or muted-forever monitors across the org Write technical designs, review the hard changes and mentor engineers around you. Your judgment will set the direction of the platform for the next few years What We're Looking For 8+ years of professional software engineering experience, including several years focused on infrastructure, platform or developer experience. A track record of staff-level ownership: you've set the technical direction for a platform or build/deploy system that many engineers depend on, and you can point to measurable gains in velocity or reliability. Deep hands-on experience with a major public cloud (AWS preferred) and operating Kubernetes in production. Fluency with infrastructure as code (Terraform) and GitOps-style delivery (ArgoCD or similar). Real experience designing CI/CD at scale: pipeline standardization, self-hosted runners, build caching, progressive delivery and safe rollbacks. Strong observability and reliability instincts. You've defined SLOs, cleaned up alerting, and turned incident follow-ups into fixes in the system rather than tickets that age out. A product mindset toward internal tooling. You measure success by adoption and by how rarely people need to ask Infra for help. AI tooling built into your development workflow in a meaningful way. You aren't just aware of the tools; you've changed how you work because of them, and you have opinions on how agents should fit into build, deploy and operations. Experience at a high-growth startup or a small, high-leverage platform team where you shipped quickly and worked through ambiguity without heavy process. At Genius AI, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. We believe this benefits not only our employees but our product, customers, and community as well. Genius AI is proud to be an Equal Opportunity and Affirmative Action Employer. Personal Information: Notice at Collection for Employees and Applicants Agency Submissions If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired. Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.

About Genius AI Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more. Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points. About the Role As a Senior Analytics Engineer, you'll own how Genius AI models, defines, and trusts its data. You sit at the intersection of data and the business, curating data so that it can be used to drive insights, strategy, and decision making. Our agentic products are scaling and our architecture is moving toward a more software-oriented model, which means the dbt project you design now will set the standard for how we understand customer behavior and how our AI-powered products make decisions. You won't inherit a finished playbook. You'll write one, and you'll ship changes in days, not quarters, with the judgment to know when to slow down. We expect you to challenge how we work, not just execute against it. You will report to the Analytics Engineering Manager. You must be commutable to our NYC headquarters and will operate in an in-person environment. We default to being in-office 3–4 days per week with required attendance on Tuesdays and Thursdays. What You'll Do Own the architecture of our dbt project, including design patterns, modeling standards, and the best practices to design efficient, effective data models that will be leveraged across the business to drive insight and action Partner with PDE (product, design, engineering) teams to support new features and architectural changes by reviewing design docs, creating or updating dbt models as data sources evolve, and validating that metrics, reports, and downstream consumers stay accurate Work with business partners in Marketing, RevOps, Sales, and Finance to scope their data requests, gather requirements, and design and build data solutions (rETLs, data models, metrics, reporting) to curate data meaningfully Build, refactor, and optimize dbt models that turn raw product and customer data into accurate, scalable datasets, connecting ideas across all of our data models Build, refactor, and optimize dbt models that turn raw product and customer data into accurate, scalable datasets and correcting fast when the data says we're wrong Use AI to build, not just work: design automated testing, documentation, and data workflows that scale beyond your own capacity and free your judgment for the problems that need it Collaborate with data engineering to shape ingestion and transformation pipelines across Snowflake, dbt, Segment, Matia, Fivetran, and Airflow as we move toward a service-oriented architecture Drive data privacy, governance, and quality standards that protect the integrity of the data our customers trust us with What We're Looking For 5+ years of experience as an analytics engineer, data engineer, or reporting engineer, with 2+ years of hands-on dbt development You've built AI-assisted workflows for modeling, testing, or documentation rather than only using AI-assisted editors Default to action: you set a direction, ship something, and iterate on what you learn instead of waiting weeks for perfect alignment Advanced SQL proficiency, with a track record of writing models that stay fast and readable as data volume grows Hands-on experience with data modeling, ETL/ELT development principles, and data warehousing concepts Familiarity with our stack (Snowflake, dbt, Hex, Segment, Matia, Fivetran, Airflow) preferred Benefits & Perks Competitive health & dental insurance options, effective on your first day of employment Flexible PTO In-office lunch twice per week for NYC and SF employees, plus late night dinner stipends Access to Wellhub, a corporate wellness platform with discounted gym memberships, fitness classes, and mental health resources Annual stipend for professional development and continued learning High performers at 5 years receive a $5,000 bonus to use however you recharge best 401k benefit: employees are eligible to contribute starting day 1 of employment Dependent Care FSA Paid parental leave Fertility and adoption benefits via Carrot and Kindbody At Genius AI, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. We believe this benefits not only our employees but our product, customers, and community as well. Genius AI is proud to be an Equal Opportunity and Affirmative Action Employer. Personal Information: Notice at Collection for Employees and Applicants Agency Submissions If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired. Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.