Careers at SoFi

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role We are looking for a Staff Backend Engineer to help build the next generation of SoFi's digital asset custody platform. This engineer will design and develop the core services that power secure custody, blockchain transaction processing, wallet infrastructure, and institutional digital asset products. This role sits at the center of crypto infrastructure, working closely with Security, Platform Engineering, Product, Treasury, and Operations to build highly available systems responsible for protecting customer assets. The ideal candidate enjoys solving distributed systems problems, designing resilient APIs, and building financial infrastructure where security and reliability are first-class requirements. What you’ll do: Design and build backend services supporting SoFi's digital asset custody platform Develop secure transaction orchestration services for deposits, withdrawals, transfers, staking, and treasury operations Build integrations with custody providers, blockchain infrastructure, and institutional settlement networks Design APIs supporting retail and institutional crypto products Develop services supporting wallet lifecycle management and blockchain interactions Improve platform resiliency through redundancy, disaster recovery, observability, and automated recovery mechanisms Optimize transaction throughput while maintaining strict security controls Build scalable event-driven architectures supporting blockchain state changes and transaction processing Partner closely with Security Engineering to implement cryptographic controls and authorization workflows Collaborate with Product and Infrastructure teams to deliver new digital asset capabilities What you’ll need: 7+ years of backend software engineering experience Strong experience with applied cryptography, key management architectures (HSMs, KMS), or Multi-Party Computation (MPC) protocols. Proven experience building high-stakes financial transaction systems (e.g., trading engines, payment rails, digital asset wallets) with a zero-trust, security-first mindset. Strong understanding of blockchain fundamentals, transaction signing lifecycles, and wallet architecture. Strong experience with distributed systems and cloud-native architectures Experience building highly available production services Strong understanding of REST APIs, asynchronous messaging, and event-driven systems Experience with AWS or comparable cloud platforms Experience with PostgreSQL, Redis, Kafka, or similar technologies Strong understanding of CI/CD and modern software development practices Excellent debugging and production incident response skills Nice to have: Experience working with digital assets or blockchain infrastructure Experience integrating with custody platforms such as Fireblocks, BitGo, or Anchorage Experience building financial services infrastructure Familiarity with blockchain transaction lifecycle and wallet architecture Experience designing secure approval workflows Understanding of distributed consensus and cryptographic systems Experience supporting institutional financial platforms Compensation and Benefits The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page! SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time. Internal Employees If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role We are looking for a Staff Backend Engineer to help build the next generation of SoFi's digital asset custody platform. This engineer will design and develop the core services that power secure custody, blockchain transaction processing, wallet infrastructure, and institutional digital asset products. This role sits at the center of crypto infrastructure, working closely with Security, Platform Engineering, Product, Treasury, and Operations to build highly available systems responsible for protecting customer assets. The ideal candidate enjoys solving distributed systems problems, designing resilient APIs, and building financial infrastructure where security and reliability are first-class requirements. What you’ll do: Design and build backend services supporting SoFi's digital asset custody platform Develop secure transaction orchestration services for deposits, withdrawals, transfers, staking, and treasury operations Build integrations with custody providers, blockchain infrastructure, and institutional settlement networks Design APIs supporting retail and institutional crypto products Develop services supporting wallet lifecycle management and blockchain interactions Improve platform resiliency through redundancy, disaster recovery, observability, and automated recovery mechanisms Optimize transaction throughput while maintaining strict security controls Build scalable event-driven architectures supporting blockchain state changes and transaction processing Partner closely with Security Engineering to implement cryptographic controls and authorization workflows Collaborate with Product and Infrastructure teams to deliver new digital asset capabilities What you’ll need: 7+ years of backend software engineering experience Strong experience with applied cryptography, key management architectures (HSMs, KMS), or Multi-Party Computation (MPC) protocols. Proven experience building high-stakes financial transaction systems (e.g., trading engines, payment rails, digital asset wallets) with a zero-trust, security-first mindset. Strong understanding of blockchain fundamentals, transaction signing lifecycles, and wallet architecture. Strong experience with distributed systems and cloud-native architectures Experience building highly available production services Strong understanding of REST APIs, asynchronous messaging, and event-driven systems Experience with AWS or comparable cloud platforms Experience with PostgreSQL, Redis, Kafka, or similar technologies Strong understanding of CI/CD and modern software development practices Excellent debugging and production incident response skills Nice to have: Experience working with digital assets or blockchain infrastructure Experience integrating with custody platforms such as Fireblocks, BitGo, or Anchorage Experience building financial services infrastructure Familiarity with blockchain transaction lifecycle and wallet architecture Experience designing secure approval workflows Understanding of distributed consensus and cryptographic systems Experience supporting institutional financial platforms Compensation and Benefits The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page! SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time. Internal Employees If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. SoFi Bank N.A. seeks Staff Data Scientist in San Francisco, CA: Job Duties: Identify opportunities and collaborate cross functionally to develop, implement, and continuously improve machine learning models and strategies that support credit underwriting. Identify opportunities to apply AI and advanced machine learning approaches to solve complex business problems. Evaluate alternative data sources and external vendor solutions by defining and driving proof of concept projects to demonstrate the solutions business values. Explore and leverage inhouse, external, and other opensource machine learning software/algorithms. Contribute in enhancing SoFi’s risk model development code base by developing customized Python scripts or packages. Collaborate with Model Risk Management team and Fair Lending team to demonstrate models are developed with high level rigor that satisfy Model Risk Management requirements, Fair Lending requirements, and other regulatory requirements. Spearhead model deployment by collaborating with cross functional teams including Credit, Product, Engineering, and Business Unit. Present model performance and insights to Credit, Risk, and Business Unit leaders. Full-time telecommuting is an option. Requirements: Master’s degree in Statistics, Data Science, or a related quantitative discipline and (5) five years of experience in the job offered or a related occupation Or Bachelor’s degree in Statistics, Data Science, or a related quantitative discipline and (7) seven years of experience in the job offered or a related occupation. Special Skill Requirements: (1) Machine Learning and statistical modeling for supervised and unsupervised learning; (2) Python; (3) Databases and related languages and tools including SQL, NoSQL, and Hive; (4) Statistical Inference (5) Full model development cycle on modern cloud platform including model development, implementation and monitoring; (6) Experience in unsecured loan credit and cashflow underwriting. (7) Familiar with credit bureau data such as Experian, TransUnion or Equifax (8) Experience in model implementation including CICD pipeline and deployment of models to production endpoints. Any suitable combination of education, training and/or experience is acceptable. Full-time telecommuting is an option. Salary: $223,560.00 - $245,916.00 per year. Submit resume with references using the apply button on this posting or by email to: Req.# 1014.40.2 at: ATTN: HR, jobadverts@sofi.org . #LI-DNI Compensation and Benefits The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page! SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time. Internal Employees If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role: We’re seeking a Staff Security Detection Engineer to build and mature SoFi’s machine learning–driven detection and anomaly detection program. You will own the detection and model lifecycle end to end; feature engineering, model training, tuning, and validation, operating over large-scale security data lakes and streaming pipelines. You’ll partner closely with our Security Operations Center (SOC), Security Operations Engineering, and Fraud programs to turn high-volume telemetry into high-confidence, low-noise detections at scale. What you’ll do: Design, build, and maintain machine learning models for anomaly detection (unsupervised clustering, time-series and seasonality baselines, isolation forests, autoencoders, risk scoring) with measurable precision/recall targets. Operationalize models and detections from notebook to production, including enrichment, correlation, and response playbook hooks (detection-as-code, CI/CD, model versioning, and rollback). Engineer and tune features from identity, endpoint, network, cloud, SaaS, and application telemetry stored in the security data lake to improve model signal quality. Partner with the SOC to triage, tune, and close detection feedback loops; use analyst dispositions as labels to retrain and improve models, reduce noise, and document runbooks. Collaborate with Threat Intelligence, Security Architecture, and Fraud stakeholders to translate threat hypotheses and scenarios into repeatable, model-backed analytics with clear success metrics. Establish model governance: offline and online evaluation, drift and data-quality monitoring, periodic retraining and re-baselining, explainability/traceability, and privacy-by-design controls. Participate in root-cause and post-incident reviews to identify new signals, features, and coverage gaps; backlog and deliver the resulting models and detections. Contribute to reference architectures, standards, and documentation for the ML detection platform, data lake, and pipelines across the security organization. Mentor engineers and analysts on applied ML, anomaly detection, detection tuning, data quality, and pipeline reliability. What you’ll need: 7+ years hands-on experience building and operating machine learning models for detection or anomaly detection in production (e.g., security, fraud, or abuse), across both supervised and unsupervised approaches. Hands-on experience with data lake and big-data technologies (e.g., Snowflake, Databricks, Spark, Delta/Iceberg, S3/GCS) for storing, transforming, and querying large-scale security telemetry. Strong programming and query skills in Python and SQL, with hands-on use of the ML and data stack (e.g., pandas, scikit-learn, PyTorch or TensorFlow) for feature engineering, model training, and automation. Solid understanding of security telemetry sources; identity and access (SSO, IGA, PAM), endpoint/EDR, network/proxy, cloud (AWS/GCP/Azure), and SaaS audit logs, and how to shape them into model features. Working knowledge of anomaly detection techniques (statistical baselining, clustering, isolation forests, autoencoders, time-series methods) and the end-to-end model lifecycle. Familiarity with security frameworks and adversary tradecraft (MITRE ATT&CK, kill chain) and how they map to detectable behaviors and model features. Experience collaborating with SOC/DFIR and fraud/risk teams; excellent written communication for models, detections, runbooks, and stakeholder updates. Ability to balance detection coverage, model precision, and operational load; metrics-driven mindset (precision/recall, false-positive rate, MTTD, alert fatigue). Bachelor’s degree in computer science, data science, statistics, a related field, or equivalent practical experience. Nice to have: Experience with streaming and real-time data engineering (e.g., Kafka, Kinesis, Pub/Sub, Flink, Spark Streaming) for near-real-time model scoring. Experience building and deploying ML models on AWS (e.g., SageMaker, S3, Glue, Athena, Lambda) for training, feature pipelines, and inference. MLOps practices – feature stores, model registries, experiment tracking, canary and shadow releases for reliable model deployment and retraining. Graph-based ML and analytics for entity relationships, risk propagation, and community detection. Experience applying deep learning or LLM-based approaches to security, log, or sequence data. Experience leveraging LLMs to design, analyze, and test detections. Relevant certifications (e.g., AWS/GCP machine learning or data engineering, Databricks, or equivalent). Compensation and Benefits The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page! SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time. Internal Employees If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role: We’re seeking a Staff Security Detection Engineer to build and mature SoFi’s machine learning–driven detection and anomaly detection program. You will own the detection and model lifecycle end to end; feature engineering, model training, tuning, and validation, operating over large-scale security data lakes and streaming pipelines. You’ll partner closely with our Security Operations Center (SOC), Security Operations Engineering, and Fraud programs to turn high-volume telemetry into high-confidence, low-noise detections at scale. What you’ll do: Design, build, and maintain machine learning models for anomaly detection (unsupervised clustering, time-series and seasonality baselines, isolation forests, autoencoders, risk scoring) with measurable precision/recall targets. Operationalize models and detections from notebook to production, including enrichment, correlation, and response playbook hooks (detection-as-code, CI/CD, model versioning, and rollback). Engineer and tune features from identity, endpoint, network, cloud, SaaS, and application telemetry stored in the security data lake to improve model signal quality. Partner with the SOC to triage, tune, and close detection feedback loops; use analyst dispositions as labels to retrain and improve models, reduce noise, and document runbooks. Collaborate with Threat Intelligence, Security Architecture, and Fraud stakeholders to translate threat hypotheses and scenarios into repeatable, model-backed analytics with clear success metrics. Establish model governance: offline and online evaluation, drift and data-quality monitoring, periodic retraining and re-baselining, explainability/traceability, and privacy-by-design controls. Participate in root-cause and post-incident reviews to identify new signals, features, and coverage gaps; backlog and deliver the resulting models and detections. Contribute to reference architectures, standards, and documentation for the ML detection platform, data lake, and pipelines across the security organization. Mentor engineers and analysts on applied ML, anomaly detection, detection tuning, data quality, and pipeline reliability. What you’ll need: 7+ years hands-on experience building and operating machine learning models for detection or anomaly detection in production (e.g., security, fraud, or abuse), across both supervised and unsupervised approaches. Hands-on experience with data lake and big-data technologies (e.g., Snowflake, Databricks, Spark, Delta/Iceberg, S3/GCS) for storing, transforming, and querying large-scale security telemetry. Strong programming and query skills in Python and SQL, with hands-on use of the ML and data stack (e.g., pandas, scikit-learn, PyTorch or TensorFlow) for feature engineering, model training, and automation. Solid understanding of security telemetry sources; identity and access (SSO, IGA, PAM), endpoint/EDR, network/proxy, cloud (AWS/GCP/Azure), and SaaS audit logs, and how to shape them into model features. Working knowledge of anomaly detection techniques (statistical baselining, clustering, isolation forests, autoencoders, time-series methods) and the end-to-end model lifecycle. Familiarity with security frameworks and adversary tradecraft (MITRE ATT&CK, kill chain) and how they map to detectable behaviors and model features. Experience collaborating with SOC/DFIR and fraud/risk teams; excellent written communication for models, detections, runbooks, and stakeholder updates. Ability to balance detection coverage, model precision, and operational load; metrics-driven mindset (precision/recall, false-positive rate, MTTD, alert fatigue). Bachelor’s degree in computer science, data science, statistics, a related field, or equivalent practical experience. Nice to have: Experience with streaming and real-time data engineering (e.g., Kafka, Kinesis, Pub/Sub, Flink, Spark Streaming) for near-real-time model scoring. Experience building and deploying ML models on AWS (e.g., SageMaker, S3, Glue, Athena, Lambda) for training, feature pipelines, and inference. MLOps practices – feature stores, model registries, experiment tracking, canary and shadow releases for reliable model deployment and retraining. Graph-based ML and analytics for entity relationships, risk propagation, and community detection. Experience applying deep learning or LLM-based approaches to security, log, or sequence data. Experience leveraging LLMs to design, analyze, and test detections. Relevant certifications (e.g., AWS/GCP machine learning or data engineering, Databricks, or equivalent). Compensation and Benefits The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page! SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time. Internal Employees If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. About The role As a Vulnerability Management Engineer, you will support the identification, assessment, prioritization, and remediation of vulnerabilities across applications and infrastructure. Working under the guidance of senior team members, you will assist in understanding how vulnerable dependencies enter an application, identifying remediation options, and engaging with engineering teams to track fixes. You will contribute to the maintenance of internal vulnerability-management tools, such as scripts, documentation, and reporting. The ideal candidate will have a desire to grow their AppSec expertise, will be eager to learn about modern security tooling and automation, and will be comfortable using AI tools like Claude to assist with documentation, investigation, and scripting tasks while following company security and data-handling requirements. What you’ll do Perform regular vulnerability assessments using different tools. Regularly drive remediation and reporting of cataloged vulnerabilities. Assess discovered vulnerabilities and properly prioritize their scope, impact and necessary response actions. Conduct security reviews of our products and production infrastructure. Contribute to vulnerability management, application security and/or offensive/red-team operations. Engage in security audit and security regulatory exercises with partners and vendors. Support regulatory compliance monitoring and reporting Support treatment and remediation activities with identified points of contact and system owners Develop processes and document procedures for use by other team members and to enhance efficiencies What you’ll need Bachelor’s Degree in Computer Science, Information Systems, or equivalent work-related experience Strong knowledge of industry standards regarding vulnerability management including Common Vulnerabilities and Exposures (CVE), Common Vulnerability Scoring System (CVSS), OWASP, etc. Experience with different types of vulnerability assessment tools or related experience in vulnerability detection DAST/SAST tools Outstanding communication and interpersonal skills, with the capacity to effectively convey intricate security concepts to both technical and non-technical stakeholders. Ability to demonstrate knowledge with prioritizing remediation activities with operational teams through risk ratings of vulnerabilities and assets Experience judging the vulnerability priority based on risk and impact Deep application security knowledge, with the ability to map an application vulnerability to exploitation indications and relevant investigative techniques. Hands-on experience with at least one coding language (Bash, Go, Python, Java). Experience with Secure Software Development Life Cycles. Preferred Qualifications 2+ years of experience in an information technology/security role 2+ years of experience with cloud technologies Ability to manage relationships with other business units, external vendors, and stakeholders when IT security risks are present and system or process changes must be made to mitigate risk Familiarity with AWS and at-scale services Experience with micro-service architecture Knowledge of CI/CD, application development and testing tools Ability to work in a fast paced and Agile development environment Work and play well with others; SoFi is a collaborative environment Nice to have Masters or PhD in Computer Science or Engineering Financial services experience Compensation and Benefits The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page! SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time. Internal Employees If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.