Senior Lead AI Engineer, GenAI Platform Services, Agentic Platform

Capital One Financial

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: San Jose, CAMcLean, VACambridge, MANew York, NY
Salary: $229,900–$262,400 / yr
Posted: 15 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $207k

This role $246k

$156k most similar roles pay here $274k

This role pays more than 83% of similar roles. Most pay $167,525–$246,150 — the shaded band above. At the midpoint, this role pays about $246k versus about $207k for comparable roles.

Based on 239 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Lead AI Engineer, GenAI Platform Services, Agentic Platform

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Senior Lead AI Engineer (GenAI Platform Services, Agentic Platform) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions that enhance internal workflows and customer interactions. This role involves designing, testing, and supporting critical software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, and observability. The engineer will implement state-of-the-art LLM optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for production systems. The technical stack includes Python, Go, Scala, Java, C++, C#, PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters. This position addresses the challenge of building responsible, scalable AI infrastructure to provide high-performance capabilities within the banking sector. The role requires a deep understanding of engineering and mathematics to identify optimization opportunities in large-scale production environments.

Skills

Python Go Scala Java C++ C# AWS Huggingface PyTorch VectorDBs LLM Inference Nemo Guardrails Machine Learning GenAI Similarity Search

What you'll do

Design, develop, test, and deploy AI software components including foundation model training and LLM inference.
Implement similarity search, guardrails, model evaluation, and observability for production AI systems.
Develop state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput.
Integrate open-source and SaaS technologies such as Huggingface, VectorDBs, and PyTorch into the platform.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
Translate complex scientific research and novel techniques into practical production applications.
Lead and mentor an engineering team while influencing cross-functional stakeholders.

What we're looking for

Bachelor's degree in Computer Science, AI, Electrical Engineering, or related fields with at least 6 years of experience developing AI/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, or related fields with at least 4 years of experience developing AI/ML algorithms.
At least 6 years of experience programming with Python, Go, Scala, or Java.
7 years of experience deploying scalable and responsible AI solutions on cloud platforms like AWS, Google Cloud, or Azure.
Experience designing, developing, and supporting complex AI systems including LLM inference, similarity search, and vector databases.
Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost.
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders.
Excellent communication skills to articulate complex AI concepts to peers and present findings clearly.

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