Senior Staff AI Engineer

Capital One

. Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products .

Posted 9/23/2026full-timeRemote • United StatesSenior💰 $286,200 - $392,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying AI and ML algorithms, with a strong focus on architecting scalable AI platforms and optimizing performance. Proven leadership in mentoring technical teams and influencing cross-functional stakeholders while ensuring adherence to AI safety and governance standards.

Highest-signal resume keywords

AI And ML Algorithm DevelopmentAI Platform ArchitecturePython ProgrammingCloud Deployment (AWS, Google Cloud, Azure)Mentoring Technical Teams

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Software DevelopmentFoundation Model TrainingLLM InferenceModel EvaluationAI Optimization TechniquesAgentic AI SystemsScalable AI SolutionsComplex AI Systems IntegrationCUDA ProgrammingJava Programming

Soft Skills

LeadershipCross-Functional CollaborationMentoring

Tools & Technologies

AWS UltraclustersHugging FaceVectorDBsPyTorchCloud Platforms

Industry Keywords

AI Safety StandardsAI GovernanceEthics in AIRegulatory ComplianceApplied AI Leadership

Tech Stack

Tools & technologies

AWSAzureCloudJavaPythonPyTorchScalaC++Go

About the role

Key responsibilities & impact

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 and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
Leverage open-source and SaaS AI technologies such as 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 at Capital One
Define and steer the technical AI architecture vision, integrating applied research breakthroughs into reliable, scalable production ecosystems
Lead the establishment of AI performance, safety, and transparency standards for company-wide model development and deployment
Drive multi-year platform initiatives unifying data, compute, and model lifecycle management under an enterprise AI architecture
Mentor senior technical leaders across research, data, and engineering disciplines

Requirements

What you’ll need

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies; or a Master's degree in these fields plus at least 8 years of such experience
At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java
Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy
9 years of experience 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
Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level
Experience developing AI and ML algorithms or technologies using Python, C++, C#, Java, CUDA, or Golang
Experience developing and applying state-of-the-art techniques for optimizing training and inference software
Experience building agentic AI systems and workflows
Recognized industry leadership in applied AI or machine learning infrastructure through patents, publications, or open-source leadership
Experience designing long-term AI infrastructure strategies while balancing cost, scale, ethics and regulatory compliance
Experience driving organization-wide adoption of AI safety, alignment and governance standards
Proven ability to shape R&D investment strategy
Experience right-sizing models, instance counts, and hardware types
Qualified applicants may be eligible for employment authorization sponsorship

Benefits

Comp & perks

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial and other benefits supporting total well-being
Reasonable accommodations for applicants who require them