Lead AI Engineer responsible for developing AI software components and delivering AI - powered products at Capital One. Collaborating with cross - functional teams to enhance customer interaction with innovative AI solutions.
About the role
- Founding Applied AI Engineer defining AI-powered leadership coaching for enterprises. Collaborating with cross-functional teams to build intelligent systems at enterprise scale.
Responsibilities
- Architect and build enterprise-grade AI and conversational systems that power coaching workflows and user experiences.
- Develop, evaluate, and refine LLM-based components - balancing performance, scalability, and reliability in real use cases.
- Integrate and manage diverse sources of structured and unstructured data to improve contextual understanding and output quality.
- Partner closely with product, engineering, and design to translate user needs into impactful technical solutions.
- Rapidly prototype and iterate on systems that span backend services, data pipelines, and frontend interactions as needed.
- Build tooling, tests, and automation to support reliable model deployment, observability, and continuous improvement.
- Help streamline data and science workflows, enabling fast experimentation and data-driven decisions.
Requirements
- 3+ years of experience in software engineering, AI/ML, data-intensive systems, AI/ML development (ideally including a Master's or Ph.D. in Computer Science, ML, Data Science, or a related field)
- Familiarity with language systems (e.g., NLP, conversational interfaces, IR) and comfort reasoning about model behavior, context, and evaluation - both theoretical and practical knowledge
- Experience with core data science tools such as NumPy, scikit-learn, Pandas, PySpark, plus SQL and common visualization tools (e.g., matplotlib, Seaborn, Plotly or BI tools) to explore and communicate insights
- Comfortable developing and deploying services in cloud environments (AWS, GCP, Azure) and working with containerization/orchestration (Docker, Kubernetes)
- Strong software engineering skills, including writing maintainable code, debugging distributed systems, and collaborating in cross-functional teams
- Eagerness to tackle unfamiliar problems, learn new technologies, and contribute to shaping our platform and culture
- Ability to explain technical ideas clearly and work effectively with both technical and non-technical stakeholders
- Nice-to-have (but not required): experience with ML lifecycle tools (e.g., MLflow, Weights & Biases), familiarity with Cloud ML services, or past work building generative AI applications
Benefits
- Competitive salary including base + bonuses
- Comprehensive health coverage (medical, dental, vision) from day one
- Generous PTO, company-wide R&R shutdowns, and paid parental leave
- Retirement plan support for US and global employees
- Meaningful ownership in a venture-backed company at a growth inflection point
- Financial upside that comes from scaling fast
- Top-up grants as we scale and you deliver exceptional performance — your compensation grows alongside your impact
- A culture built for top talent: intensity to win, growth without limits, and a team that solves hard problems and celebrates big wins together
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