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Capital One

AI Engineer 5 – Gen AI Platform Services, Agentic AI

Capital One

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

Posted 9/18/2026full-timeMcLean • California • United StatesMid-LevelSenior💰 $229,900 - $286,200 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and optimizing AI systems, including foundation model training and LLM inference, while ensuring compliance with ethical AI standards. Proven ability to lead technical teams and manage cost-performance governance for scalable AI solutions.

Highest-signal resume keywords
AI System DevelopmentPython ProgrammingLLM InferenceCloud DeploymentEthical AI Standards

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
AI AlgorithmsMachine Learning TechnologiesFoundation Model OptimizationMulti-Model OrchestrationModel EvaluationSimilarity SearchAgentic AI SystemsDynamic Inference StrategiesModel CompressionGPU Utilization
Soft Skills
MentoringLeadershipCollaboration
Tools & Technologies
AWS UltraclustersHugging FaceVectorDBsPyTorch
Industry Keywords
AI Engineering StandardsCost-Performance GovernanceHuman-in-the-Loop ReviewsExplainabilityFairness

Tech Stack

Tools & technologies
AWSCloudJavaPythonPyTorchScalaGo

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 foundation model optimization techniques to improve scalability, cost, latency, and throughput
  • Contribute to the technical vision and long-term roadmap of foundational AI systems
  • Design, implement, and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models
  • Establish and lead cost-performance governance reviews, tracking GPU utilization, model throughput, and inference cost efficiency
  • Lead team design councils or design review boards for technical consistency and AI engineering standards compliance
  • Mentor Principal- and Manager-level AI engineers and elevate organizational technical maturity

Requirements

What you’ll need
  • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, OR a Master's degree in a related field plus at least 4 years of such experience
  • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java
  • Experience leading AI system development with cost, latency, throughput, and accuracy tradeoffs
  • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms
  • Experience designing, developing, delivering, and supporting complex AI systems
  • Experience developing AI/ML algorithms or 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
  • Experience architecting and integrating heterogeneous AI systems into unified production pipelines
  • Experience defining and enforcing ethical AI deployment standards, including explainability, fairness, and human-in-the-loop reviews
  • Ability to balance model performance and operational cost through dynamic inference strategies and model compression
  • 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 bonuses and/or long-term incentives (LTI)
  • Comprehensive health, financial, and other benefits supporting total well-being