The Impact You’ll Make

• Define and lead product security strategy across web, mobile, API, cloud, infrastructure, and container security — conducting threat modeling, risk assessments, and security reviews throughout the development lifecycle with a strong shift-left focus.
• Embed secure development practices by designing and implementing secure coding standards, encryption, and security testing methodologies in close collaboration with development and ML teams, ensuring products are secure, resilient, and trustworthy.
• Own Enterprise AI Security end-to-end — from securing LLM integrations, agentic pipelines, and ML model ingestion to defending against AI-specific threats (prompt injection, data poisoning, model extraction, RAG poisoning, ), building AI incident response playbooks, and red-teaming AI systems across Recursion's product surfaces.
• Secure the AI supply chain and MLOps infrastructure by vetting third-party foundation models, open-source weights, and AI APIs before production integration, and partnering with ML engineering to protect training pipelines, feature stores, and model serving endpoints.
• Champion compliance and AI governance by operationalizing frameworks such as OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, and EU AI Act requirements — collaborating with legal, privacy, and responsible AI teams to support audits and evolving regulatory expectations.
• Scale security as a force multiplier by evaluating and deploying security tooling, detecting policy violations, driving security outcomes, and ensuring security initiatives never become a bottleneck to business objectives.
• Elevate the security culture across the organization by serving as a subject matter expert, mentoring engineering teams, and leading incident response efforts from investigation through mitigation and prevention.
• Maintain the security foundation through thorough documentation — including security requirements, guidelines, and incident response plans — and hands-on penetration testing and code reviews to simulate and get ahead of real-world threats.

The Team You'll Join

• You will join a growing Information Security team at Recursion, focused on enabling Recursion to decode biology by providing world class technology services that are designed and fit for purpose. You'll collaborate with your teammates and across departments to agree on what the most important challenges and capabilities are, then figure out how to get us there.

The Experience You'll Need

• Education & Tenure: Bachelor's or Master's degree in Computer Science, Information Security, or a related field, with 10+ years of experience in product security or application security and a proven track record securing complex products.
• Security Fundamentals: Deep understanding of security principles, threats, and countermeasures as they relate to product design and development, with familiarity across standards and frameworks including OWASP, NIST, ISO/IEC 27001, and CVSS-based vulnerability prioritization.
• Offensive Security & Penetration Testing: Hands-on proficiency with penetration testing frameworks and tools (Metasploit, Burp Suite, Nmap, Wireshark), web application attack techniques (SQL injection, XSS, CSRF, OWASP Top Ten), and the ability to simulate real-world attacks and assess their impact.
• Secure Development & Engineering: Expertise in one or more programming languages (e.g., Python, Java, C++) with strong command of secure coding practices, encryption standards, and integrating security tooling into CI/CD and development workflows.
• Enterprise AI Security: Demonstrated experience securing AI/ML systems and LLM-powered or agentic products in production — including familiarity with AI attack surfaces (prompt injection, data poisoning, model extraction, membership inference, RAG poisoning) and hands-on red-teaming of AI pipelines and agentic workflows.
• AI Frameworks & Supply Chain Risk: Working knowledge of AI security frameworks (OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, EU AI Act) and experience vetting third-party foundation models, open-source weights, and AI APIs as part of a structured supply chain security program.
• MLOps & Model Security: Familiarity with securing ML infrastructure — including training pipelines, experiment tracking, model registries, and inference endpoints — and designing least-privilege access controls for AI agents with external system or tool access.
• Leadership & Communication: Excellent communication and influencing skills, with the ability to drive security initiatives across engineering, legal, privacy, and executive stakeholders and mentor teams on security best practices.
• Certifications (Highly Desirable): CISSP, OSCP, or GWAPT for core security credentialing, plus AI-focused certifications such as GAISC, Offensive ML (OffSec), or cloud provider AI security tracks (AWS/GCP).

Working Location & Compensation:

Making SLC your home base is ideal, however, we will consider remote work for this position. We ask that remote employees commit to regular on-site visits for routine work and departmental events.

At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $186,900 to $220,400 (USD). You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. 

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ABOUT THIS ROLE 

As the Sr. Manager of Data Engineering and Architecture, you will be a hands-on leader responsible for defining and executing the data engineering strategy, architecture, and technology stack. You will be responsible for the foundational data infrastructure that powers analytics and decision-making across the organization.

A critical part of this role will be building, mentoring, and managing a team of 3 data engineers. You will guide the team's efforts while also contributing directly to the development of our modern data warehouse in Snowflake using dbt and SQL, transforming raw data into reliable and accessible datasets. Crucially, you will spearhead the data migration efforts for our ongoing Oracle Fusion Cloud deployment, designing a robust, cohesive data ecosystem that bridges our new Oracle environment with Snowflake.

Your leadership will ensure the successful design, build, and maintenance of robust data pipelines that ingest data from a variety of internal and external sources into Snowflake. Your team's work will support reporting, dashboarding, and analysis across the company, enabling teams to make informed decisions based on trusted data. Given the green-field nature of this initiative, the role is expected to be approximately 30% technical leadership, strategy, and people management, and 70% direct, hands-on engineering and architecture.

This position is based in a hybrid work environment and requires regular in-office collaboration. It offers an opportunity to lead with modern data tools, build a high-performing team, and make a direct, strategic impact on data quality and accessibility during a massive phase of enterprise scaling.

ROLE RESPONSIBILITIES

• Data Strategy & Architecture: Define the long-term vision, strategy, and architecture for the company’s data platform. Design a cohesive hybrid architecture that maximizes the strengths of our full tech stack, ensuring it drives measurable business value and scales efficiently to support hyper-growth.

• Team Leadership & Management: Build, mentor, and manage a team of 3 data engineers, fostering a culture of technical excellence, accountability, and continuous improvement.

• Data Modeling & Transformation: Lead the team in building and maintaining robust data models using dbt and SQL that support complex analytics and reporting needs. Contribute directly as an individual contributor as needed.

• Snowflake Development: Oversee the design and optimization of the Snowflake data warehouse to ensure performance, scalability, and usability. Participate directly in key development efforts.

• Cross-Functional Collaboration: Act as the primary technical partner to analysts, business stakeholders, and data teams to deeply understand requirements and translate them into strategic engineering solutions and delivery plans.

• Performance Tuning: Guide the optimization of SQL queries and data transformations to improve execution speed and resource efficiency across the platform.

• Tooling & Automation: Identify, evaluate, and implement opportunities to automate data workflows, improve pipeline reliability, and establish a formal DataOps/MLOps framework using modern orchestration tools (e.g., Airflow, Prefect, cloud-native serverless functions).

• BI Tool Support: Ensure the team provides clean, well-structured data models to enable effective use of BI tools like Looker, Sigma, Tableau, or similar platforms.

• Pipeline Engineering: Direct the development and maintenance of scalable data ingestion pipelines that pull data from APIs and other sources into Snowflake, including exploring solutions for near real-time data feeds.

• Data Governance & Quality: Champion best practices in data governance, data lifecycle management, and dimensional modeling. Implement data validation checks, documentation standards, and lineage tracking to maintain high data integrity across all of our systems.

• Oracle Fusion Cloud Migration & Integration: Lead the complex data migration strategy for our active Oracle deployment. Architect, build, and maintain secure, high-performing data flows and syncs between Oracle and Snowflake to ensure operational continuity and analytical excellence.

OUR IDEAL CANDIDATE

• Experience: 8+ years in data engineering or related roles, with a strong focus on data modeling and pipeline development.

• Education: Bachelor’s degree in Computer Science, Engineering, Data Analytics, or a related field.

• Technical Skills:

  • Proven experience leading complex data migration or implementation projects.

  • Advanced proficiency in SQL and experience with data modeling (e.g., star/snowflake schemas).

  • Hands-on experience with dbt for building modular and testable data transformations.

  • Experience developing data pipelines using Python and workflow orchestration tools (e.g., Airflow, Prefect).

  • Deep understanding of Snowflake.

  • Demonstrated ability to design and implement a modern data architecture from scratch.

• BI & Analytics Tools:

  • Familiarity with BI platforms such as Looker, Tableau, or Sigma is helpful.

• Infrastructure & Governance:

  • Understanding of ELT/ETL workflows, data governance, and monitoring practices.

  • Experience defining and enforcing organizational standards for data quality, metadata management, and cost optimization within a cloud data warehouse (Snowflake).

• Communication & Problem Solving:

  • Ability to clearly explain technical details to both technical and non-technical stakeholders.

  • Strong analytical and debugging skills; attention to detail in code and data quality.