Staff AI Engineer – Enterprise Analysis Platform

🔥 1 hour ago

🏄 California, New York, +2 more states – Remote

🏄 California – Remote 🗽 New York – Remote 🍂 Massachusetts – Remote ⚔️ Virginia – Remote

💵 $244.7k - $335.1k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 1%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Capital One

WebsiteLinkedInAll Job Openings

10,000+ employees

🏦 Banking

💳 Fintech

💸 Finance

💰 Post-IPO Equity on 2023-05

Banking • Fintech • Finance

Capital One is a leading financial services company that specializes in offering credit cards, auto loans, banking, and savings accounts. With a focus on innovation and technology, Capital One aims to change banking for good by providing customer-friendly solutions and fostering a diverse and inclusive workforce. The company is known for its commitment to creating a positive impact in the banking industry through advanced digital tools and customer service excellence.

📋 Description

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products • Design, develop, test, deploy, and support AI software components, including foundation model training, LLM inference, agents, multi-agent workflows, similarity search, guardrails, evaluation, experimentation, governance, and observability • Leverage open-source and SaaS AI technologies including AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch • Invent and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput • Contribute to the technical vision and long-term roadmap of foundational AI systems • Set technical direction for enterprise-wide AI architecture, tooling, observability, and deployment standards • Own design and integration of model routing, caching, and orchestration systems for hybrid and multi-model workloads • Champion responsible AI principles, including transparency, reproducibility, and fairness-by-design • Drive internal education, mentorship, and best-practice dissemination through architecture councils and AI guilds

🎯 Requirements

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies; or Master's degree in a related field plus at least 6 years of such experience • At least 8 years of programming experience with Python, Go, Scala, CUDA, or Java • Experience designing AI systems with cost, latency, throughput, and accuracy tradeoffs • 8+ years deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems • Ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to VP level • Experience developing AI/ML technologies including LLM inference, similarity search, VectorDBs, guardrails, and memory • Experience optimizing training and inference software for hardware utilization, latency, throughput, and cost • Experience building agentic AI systems and workflows • Excellent communication and presentation skills for articulating complex AI concepts • Track record defining and operationalizing enterprise AI architecture standards, data pipeline governance, observability, and evaluation frameworks • Experience leading federated or multi-cloud AI strategies • Success influencing research-to-production promotion, model handoff, evaluation, and productization • Experience defining north-star metrics for AI systems • Experience right-sizing models, instance counts, and hardware types • Capital One will consider sponsoring a new qualified applicant for employment authorization

🏖️ Benefits

• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI) • Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being • Employment authorization sponsorship may be considered for a new qualified applicant • Reasonable accommodations for applicants who require them