Capital One Sr Distinguished Engineer Generative AI Platform Agents Tooling Eligible 

United States, California, San Francisco 

520586600

201 Third Street (61049), United States of America, San Francisco, California Sr. Distinguished Engineer, Generative AI, Platform Agents and Tooling (Remote Eligible)

Sr. Distinguished Engineer, AI Platforms to help us build the foundations of our enterprise AI Capabilities. In this role you will work on developing generic platform services to support applications powered by Generative AI. You will develop SDKs and APIs to build agents, information retrieval and to build models as a service for powering generative AI workflows such as optimizing LLMs via RAG.

Additionally you will manage end-to-end coordination with operations and manage creation of high quality curated datasets and productionizing of models along with working with applied research and product teams to identify and prioritize ongoing and upcoming services.

Examples of what you’ll do:

• Develop abstracted platform services to support applications powered by Generative AI

• Develop SDKs and APIs for our user community to power a wide range of applications such as information retrieval, fraud detection, AI Assistants, recommendations on our AI platforms.

• Design and build RAG service platform orchestrations including prompt engineering, guardrails, vector databases, API Grounding

• Build out a Prompt management service via cross organizational partnerships

• Stay up-to-date with latest advancements in operationalization of machine learning and GenAI Technologies

• Design and implement capabilities to support MLOps for foundation models.

Basic Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering or a technical field

• At least 9 years of experience programming with Python, Go, Scala, or C/C++

• At least 6 years of experience designing and building and deploying enterprise AI or ML applications.

• At least 3 years of experience implementing full lifecycle ML automation using MLOps(scalable development to deployment of complex data science workflows)

• At least 4 years of experience leading teams developing Machine Learning solutions

• At least 1 year with LLM based conversational AI systems

Preferred Qualifications:

• Master’s degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques.

• Strong problem solving and analytical skills with the ability to work independently with ownership, and as a part of a team with a strong sense of responsibilities.

• Experience with Graph or Network Theory and Graph ML, including relevant frameworks and libraries such as Deep Graph Learning (DGL) or NetworkX

• Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP.

• Experience building an abstracted SDK and familiarity with Haystack, Langchain, or similar.

• Experience architecting cloud systems for security, availability, performance, scalability, and cost.

• Experience with optimizing and delivering very large models through the MLOps life cycle from exploration to serving.

• Experience using Kubeflow Pipelines to deliver models to production.

• Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred.

• Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of an AI Platform.

• Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting, advanced RAG and fine-tuning.

• Experience working with applications that leverage LLMs and vertical integration with enterprise applications

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.