AI Engineer 5, MLX, Agentic AI, Gen AI platform Services

Capital One

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

Posted 10/4/2026full-timeUnited 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 software components, including foundation model training and multi-model orchestration. Proven ability to lead AI systems development while balancing performance and operational costs.

Highest-signal resume keywords

AI Software DevelopmentPython ProgrammingFoundation Model OptimizationMulti-Model OrchestrationAI Systems Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI AlgorithmsMachine Learning TechnologiesCUDA ProgrammingJava ProgrammingGo ProgrammingScala ProgrammingC++ ProgrammingC# ProgrammingModel EvaluationModel Compression

Soft Skills

Excellent CommunicationPresentation SkillsMentoring

Tools & Technologies

AWS UltraclustersHugging FaceVectorDBsPyTorchCloud Platforms

Industry Keywords

AI Engineering StandardsEthical AI DeploymentCost-Performance GovernanceGPU UtilizationInference Cost Efficiency

Tech Stack

Tools & technologies

AWSCloudJavaOpen SourcePythonPyTorchScalaC++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 large-scale 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 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 those fields plus at least 4 years of experience
At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java
Preferred: experience leading AI systems development with cost, latency, throughput, and accuracy tradeoffs
Preferred: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms
Preferred: experience designing, developing, delivering, and supporting complex AI systems
Preferred: experience developing AI and ML algorithms or technologies using Python, C++, C#, Java, CUDA, or Golang
Preferred: experience optimizing training and inference software for hardware utilization, latency, throughput, and cost
Preferred: experience building agentic AI systems and workflows
Preferred: experience architecting and integrating heterogeneous AI systems into unified production pipelines
Preferred: experience defining and enforcing ethical AI deployment standards
Preferred: ability to balance model performance and operational cost through dynamic inference strategies and model compression
Preferred: experience right-sizing models, instance counts, and hardware types
Strong foundation in engineering and mathematics
Ability to understand scientific publications and apply novel techniques in production
Excellent communication and presentation skills
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
Employment authorization sponsorship may be considered for a new qualified applicant
Reasonable accommodation support for applicants with disabilities