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AI Engineer 4 – Gen AI Platform Services: Agentic AI, Agent Guardrails, Agent Evaluation, Agent Memory
Capital One. Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and optimizing AI and ML algorithms, with a strong focus on scalable AI solutions and cloud deployment. Proficient in leading architectural decisions and ensuring compliance and governance in AI systems.
Highest-signal resume keywords
AI And ML Algorithm DevelopmentPython ProgrammingCloud Platform DeploymentDistributed Systems DesignAI Model Governance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Software DevelopmentFoundation Model TrainingLLM InferenceModel EvaluationPerformance TuningScalable DesignAgentic AI SystemsTraining OptimizationInference OptimizationData Governance
Soft Skills
MentoringCollaborationInfluencing Architectural Decisions
Tools & Technologies
AWS UltraclustersHugging FaceVectorDBsPyTorchGPU UtilizationTPU Utilization
Industry Keywords
AI SystemsMachine LearningEthical AlignmentSLO DefinitionModel Performance Drift
Tech Stack
Tools & technologiesAWSCloudDistributed SystemsJavaOpen 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 such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch
- 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
- Own end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethical alignment
- Define and maintain SLOs 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 field 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 programming experience with Python, Go, Scala, CUDA, or Java
- Experience leading AI systems development with cost, latency, throughput, and accuracy tradeoff decisions
- Experience deploying scalable and responsible AI solutions on cloud platforms
- Experience designing, developing, delivering, and supporting AI services
- 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 agentic workflows
- Proficiency designing distributed systems for model training, evaluation, and online inference at petabyte scale
- Experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules
- Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms
- Ability to work in the United States; Capital One will consider sponsoring a new qualified applicant for employment authorization
Benefits
Comp & perks- Performance-based incentive compensation, including cash bonus(es) and/or long-term incentives (LTI)
- Comprehensive, competitive health, financial, and other benefits supporting total well-being
- Employment authorization sponsorship consideration for a new qualified applicant