Senior Director, AI Engineering – Agentic AI Platform

Capital One

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

Posted 11/5/2026full-timeRemote • United StatesSenior💰 $286,200 - $326,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in developing and deploying scalable AI solutions, with a strong focus on foundation model optimization, AI strategy, and team leadership. Proven ability to influence organizational design and drive responsible AI practices across diverse business lines.

Highest-signal resume keywords

AI And ML Algorithm DevelopmentPeople Leadership ExperienceCloud Platform Deployment (AWS, Google Cloud, Azure)Python, C++, C#, Java, CUDA, Golang ProficiencyEnterprise AI Strategy Development

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

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

Hard Skills

AI Software Component DevelopmentFoundation Model TrainingLLM InferenceSimilarity SearchModel EvaluationExperimentationGovernanceObservabilityAgentic AI SystemsModel Lifecycle Management

Soft Skills

Excellent Communication SkillsPresentation SkillsTeam DevelopmentInfluencing Executive Leadership

Tools & Technologies

Open-Source AI TechnologiesSaaS AI TechnologiesVectorDBsAI Operations ToolsCloud Infrastructure

Industry Keywords

Responsible AI PracticesEthical AIAI Talent AcquisitionAI Investment StrategyRisk Management

Tech Stack

Tools & technologies

AWSAzureCloudJavaPythonC++Go

About the role

Key responsibilities & impact

Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
Oversee design, development, testing, deployment, and support of AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability
Make build-versus-buy decisions across open-source and SaaS AI technologies
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
Attract and retain AI talent and support team members' personal and professional development
Define and drive enterprise-wide AI strategy across product, research, risk, and data organizations
Establish a multi-year roadmap for scalable, reliable, and compliant enterprise AI infrastructure
Champion responsible, ethical, transparent, and explainable AI practices
Oversee AI operations, including model lifecycle management, observability, and cost efficiency across hundreds of production use cases

Requirements

What you’ll need

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies; or a Master's degree in one of these fields plus at least 8 years of experience
At least 5 years of people leadership experience
7+ years of experience managing and leading an engineering team
8+ years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud
Experience developing AI and ML algorithms or technologies, including LLM inference, similarity search, VectorDBs, guardrails, and memory
Experience using Python, C++, C#, Java, CUDA, or Golang
Experience building agentic AI systems and agentic workflows
Ability to apply novel AI research techniques in production
Excellent communication and presentation skills
Experience leading leaders and multiple AI engineering organizations across product, platform, and applied research domains
Proven success building enterprise-scale AI platforms serving diverse business lines and customer use cases
Ability to influence executive leadership on AI investment strategy, organizational design, and risk management priorities
Experience establishing external partnerships or thought leadership in AI industry, academia, or open-source communities
Experience right-sizing models, instance counts, and hardware types based on system requirements
Willingness to comply with applicable employment authorization requirements

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
Remote or hybrid work arrangements, subject to company policy
Employment authorization sponsorship may be considered for a new qualified applicant