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AI Engineer 5, MLX, Agentic AI, Gen AI platform Services
Capital OneCore Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing, developing, and optimizing AI systems, with a strong focus on foundation model training, multi-model orchestration, and ethical AI deployment. Proven ability to lead teams and mentor engineers while balancing performance and operational costs.
Highest-signal resume keywords
AI And ML Algorithm DevelopmentPython ProgrammingCloud Platform DeploymentAI System OptimizationTeam Leadership And Mentorship
Tech Stack
Tools & technologiesAbout 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, 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
- Design, implement, and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models
- Establish and lead cost-performance governance reviews across AI systems
- Lead team design councils or design review boards
- Mentor Principal and Manager-level AI engineers
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
- 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 heterogeneous AI systems into unified production pipelines
- Experience defining and enforcing ethical AI deployment standards
- Demonstrated ability to balance model performance and operational cost
- 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 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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Foundation Model TrainingMulti-Agent WorkflowsSimilarity SearchModel EvaluationExperimentationGovernanceObservabilityAI System DesignCost-Performance GovernanceEthical AI Standards
Soft Skills
CollaborationMentoringTechnical Vision Contribution
Tools & Technologies
AWS UltraclustersHugging FaceVectorDBsPyTorchCUDAJavaGoScalaC++C#
Certifications & Qualifications
Bachelor's Degree In Computer ScienceMaster's Degree In AI Or Related Fields
Industry Keywords
AI-Powered ProductsScalable AI SolutionsAgentic AI SystemsHeterogeneous AI SystemsProduction Pipelines