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Capital One

AI Engineer 5 – Gen AI Platform Services, Agentic AI, Guardrails, Evaluation

Capital One

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

Posted 10/6/2026full-timeUnited 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 multi-model orchestration. Proficient in leveraging cloud platforms and open-source technologies to deliver scalable and responsible AI solutions.

Highest-signal resume keywords
AI And ML Algorithm DevelopmentPython ProgrammingCloud Platform DeploymentAI System OptimizationEthical AI Standards

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
AI Software DevelopmentFoundation Model TrainingMulti-Agent WorkflowsModel EvaluationSimilarity SearchPython ProgrammingCUDA ProgrammingJava ProgrammingC++ ProgrammingGolang Programming
Soft Skills
MentoringCross-Domain LearningTechnical Leadership
Tools & Technologies
AWS UltraclustersHugging FaceVectorDBsPyTorch
Industry Keywords
AI Engineering StandardsCost-Performance GovernanceDynamic Inference StrategiesModel CompressionHuman-In-The-Loop Review

Tech Stack

Tools & technologies
AWSCloudJavaPythonPyTorchScalaC++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 including AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch
  • Invent and introduce foundation model optimization techniques to improve scalability, cost, latency, and throughput of production AI systems
  • 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 to ensure technical consistency and compliance with AI engineering standards
  • Mentor Principal- and Manager-level AI engineers and foster cross-domain learning

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 one of these fields plus at least 4 years of experience
  • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java
  • Experience leading development of AI systems with tradeoff decisions around cost, latency, throughput, and accuracy
  • 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 and ML algorithms or technologies using Python, C++, C#, Java, CUDA, or Golang
  • Experience optimizing training and inference software for hardware utilization, latency, throughput, and cost
  • Experience building agentic AI systems and workflows
  • Experience architecting and integrating rule-based, retrieval-augmented, and generative components into unified production pipelines
  • Experience defining and enforcing ethical AI deployment standards, including explainability, fairness, and human-in-the-loop review processes
  • Demonstrated 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
  • Reasonable accommodations for applicants who require them