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Capital One

AI Engineer

Capital One

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

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

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in developing and optimizing AI and ML algorithms, with a strong focus on scalable solutions and cost-performance governance. Proficient in leading cross-functional teams and mentoring engineers while ensuring compliance with AI engineering standards.

Highest-signal resume keywords
AI And ML Algorithm DevelopmentPython ProgrammingCloud Platform DeploymentAI Systems OptimizationCost-Performance Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
AI Software DevelopmentFoundation Model TrainingLLM InferenceMulti-Agent WorkflowsModel EvaluationExperimentationGovernanceObservabilityDynamic Inference StrategiesModel Compression
Soft Skills
Excellent CommunicationPresentation SkillsMentoring
Tools & Technologies
AWS UltraclustersHugging FaceVector DatabasesPyTorchCUDAGoScalaJavaC++C#
Industry Keywords
AI Engineering StandardsEthical AI DeploymentScalabilityLatencyThroughputCost Efficiency

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, 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, vector databases, 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 design councils or 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 those fields plus at least 4 years of such experience
  • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java
  • Capital One will consider sponsoring a new qualified applicant for employment authorization
  • Experience leading AI systems 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 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 heterogeneous AI systems into unified production pipelines
  • Experience defining and enforcing ethical AI deployment standards
  • Ability to balance model performance and operational cost through dynamic inference strategies and model compression
  • Experience right-sizing models, instance counts, and hardware types
  • Excellent communication and presentation skills

Benefits

Comp & perks
  • Performance-based incentive compensation, including 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