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AI Engineer
Capital One. Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products .
Tech Stack
Tools & technologiesAWSCloudJavaOpen 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
- 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 for technical consistency and AI engineering standards compliance
- 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 these 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 cost, latency, throughput, and accuracy tradeoff decisions
- 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 rule-based, retrieval-augmented, and generative AI components into unified production pipelines
- Experience defining and enforcing ethical AI deployment standards, including explainability, fairness, and human-in-the-loop review
- Ability to balance model performance and operational cost through dynamic inference strategies and model compression
- 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