Lead enterprise-grade data and AI engineering in a cloud environment supporting banking-grade identity, access decisioning, and AI/ML security. This Senior Director role focuses on multi-year platform strategy and architecture, with the goal of delivering scalable, real-time data and ML systems. The position is based in McLean, VA (onsite) and offers a salary range of USD 314,800 - 359,300 per year.
What you’ll do
- Own the enterprise strategy and multi-year roadmap for identity analytics, access decisioning, and AI/ML security platforms, aligning AI/ML investment with business, audit, and regulatory priorities.
- Partner with C-suite and CISO-org stakeholders to fund next-generation capabilities and guide platform evolution.
- Lead and scale a 50+ person organization across Data Engineering, ML, Generative AI, and Security Products, including managers and senior individual contributors.
- Set engineering standards and a high bar for well-managed delivery through hiring, development, and retention of top technical talent.
- Provide hands-on technical direction by reviewing architectures, model designs, and system trade-offs, staying close to code and data to make sound decisions under uncertainty.
- Architect low-latency, event-driven systems for real-time identity decisioning and threat detection using streaming telemetry, behavioral signals, and contextual graph data.
- Design, build, and maintain ML infrastructure and pipelines for end-to-end workflows: feature extraction, training, testing, guardrails, evaluation, deployment, and real-time and batch inference.
- Drive MLOps evolution with automated, metrics-backed deployment workflows, integration validation and testing, and scalable monitoring and observability for models in production.
- Build the intelligence layer for agentic and non-human identity by combining behavioral analytics, ML-based intent determination, and context graphs for securing AI agents and workload identities.
- Apply LLM and GenAI techniques in production for threat-intelligence summarization, automated incident triage, and adaptive access-policy recommendation, including optimization to improve scalability, cost, latency, and throughput.
- Operate an automated governance function using pipelines from enterprise and IGA platforms, operationalizing NIST controls with continuous control validation and audit-ready evidence.
- Lead enterprise readiness for emerging cyber risk from frontier AI models and agentic attack patterns.
What you bring
- Bachelor’s Degree in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
- 9+ years of experience in data engineering.
- 7+ years of people management experience.
- 7+ years of programming experience with at least one of: Python, Java, or Scala.
- 5+ years driving technical delivery of roadmap features.
- 6+ years designing and developing data pipelines.
- 4+ years in data modeling and designing end-to-end data solutions using both relational and non-relational database systems.
Tools and platforms
Python, Java, Scala, NIST, AWS, Microsoft Azure, Google Cloud, EMR, Spark, Glue, Databricks, Airflow, Dagster, Monte Carlo, Splunk, MongoDB, Cassandra, DynamoDB, Snowflake, Redshift, SQL.
Compensation and benefits
- Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
- Comprehensive, competitive, and inclusive health and financial benefits designed to support total well-being.
Posting details
- Posted date: 9/25/2026
- Location: McLean, VA (onsite)
- Employment authorization: Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
- Application window: Expected to accept applications for a minimum of 5 business days.
- Equal opportunity: Capital One is an equal opportunity employer committed to non-discrimination in compliance with applicable federal, state, and local laws (EOE, including disability/vet).
- Other: No agencies please. Capital One promotes a drug-free workplace. Capital One will consider qualified applicants with criminal history in a manner consistent with applicable laws.
Preferred qualifications
- Master’s Degree in Computer Science or a related field
- 12+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java
- 8+ years of hands-on experience designing, deploying and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud)
- 8+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
- 8+ years of experience designing, implementing, and operating real-time or streaming data pipelines
- 6+ years of experience working on data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster)
- 8+ years of experience working with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB)
- 8+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift)
- 6+ years of experience working in an Agile development environment
- 6+ years of experience developing user-centric reusable data products
- 5+ years of experience in Data Governance, Data Governance Platforms, Data Standardization, and Data Modeling
