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 StatesLead💰 $244,700 - $279,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, developing, and deploying AI systems with a focus on scalability, cost, and performance. Proficient in leading cross-functional teams and establishing enterprise AI architecture standards while championing responsible AI principles.

Highest-signal resume keywords

AI System DesignPython ProgrammingCloud DeploymentAI Architecture StandardsModel Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI AlgorithmsMachine Learning TechnologiesFoundation Model TrainingLLM InferenceSimilarity SearchModel EvaluationExperimentationGovernanceObservabilityAgentic AI Systems

Soft Skills

MentorshipCross-Functional CollaborationInfluencing Stakeholders

Tools & Technologies

AWS UltraclustersHugging FaceVectorDBsPyTorchAWSGoogle CloudAzure

Industry Keywords

Responsible AI PrinciplesTransparencyReproducibilityFairness-by-DesignFederated AI Strategies

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
Set technical direction for enterprise-wide AI architecture, tooling, observability, and deployment standards
Own 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

What you’ll need

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 a Master’s degree in those fields plus at least 6 years of experience
At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java
Experience designing AI systems with tradeoff decisions around cost, latency, throughput, and accuracy
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
Experience developing AI and ML algorithms or technologies using Python, C++, C#, Java, CUDA, or Golang
Experience optimizing training and inference software
Experience building agentic AI systems and workflows
Experience leading and mentoring multiple engineering teams and influencing cross-functional stakeholders up to VP level
Experience defining enterprise AI architecture standards, governance, observability, and evaluation frameworks
Experience leading federated or multi-cloud AI strategies
Experience influencing research-to-production promotion processes
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

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
Drug-free workplace
Equal opportunity employment and non-discrimination