AI Engineer

Capital One

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

Posted 9/21/2026full-timeUnited StatesMid-LevelSenior💰 $197,300 - $245,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying AI-powered solutions, with a strong focus on foundation model optimization, AI system architecture, and compliance with governance standards. Proficient in leveraging cloud platforms and open-source technologies to enhance AI performance and scalability.

Highest-signal resume keywords

AI Software DevelopmentFoundation Model OptimizationPython ProgrammingAI System ArchitectureCloud Platform Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI AlgorithmsMachine Learning TechnologiesModel TrainingModel InferencePerformance TuningScalable DesignData GovernanceLatency OptimizationThroughput ImprovementCost Management

Soft Skills

MentoringCollaborationTechnical Leadership

Tools & Technologies

AWS UltraclustersHugging FaceVectorDBsPyTorchGPU UtilizationTPU Utilization

Industry Keywords

AI GovernanceModel EvaluationObservabilityEthical AIAI Reliability

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsJavaPythonPyTorchScalaGo

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
Own end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethical alignment
Define and maintain service-level objectives for AI reliability, including latency, uptime, and model performance drift
Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines
Lead technical reviews for AI system deployments, ensuring security, data governance, and compliance standards
Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation

Requirements

What you’ll need

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies; or a Master's degree in those fields plus at least 2 years of such experience
At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java
Ability to understand scientific publications and apply novel techniques in production
Strong foundation in engineering and mathematics
Expertise in hardware, software, and AI
Preferred: experience leading AI system development with cost, latency, throughput, and accuracy tradeoffs
Preferred: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms
Preferred: experience designing, developing, delivering, and supporting AI services
Preferred: experience with AI/ML technologies including LLM inference, similarity search, VectorDBs, guardrails, and memory
Preferred: experience optimizing training and inference software for hardware utilization, latency, throughput, and cost
Preferred: experience building agentic AI systems and workflows
Preferred: proficiency designing distributed systems for model training, evaluation, and online inference at petabyte scale
Preferred: experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules
Preferred: ability to influence architectural decisions across multiple AI product lines or platforms

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
Employment authorization sponsorship may be considered for a new qualified applicant