✦ Luna Orbit — AI & Machine Learning

Lead AI Engineer (AI Foundations)

at Capital One Financial

📍 5 Locations Unknown 💰 $179K – $204K USD / year Posted April 02, 2026
Salary $179K – $204K USD / year
Type Full-Time
Experience lead
Exp. Years 2+ years
Education Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields; or Master's degree in related fields
Category AI & Machine Learning

Lead AI Engineer focused on AI foundations and large language model workloads, building scalable AI components with a cross-functional team at Capital One.

  • Partner with cross-functional team to deliver AI-powered products
  • Design, develop, test, deploy AI software components including LLM inference and guardrails
  • Leverage Open Source and SaaS AI technologies (HuggingFace, VectorDBs, Nemo Guardrails)
  • Optimize LLM performance for cost, latency, throughput
  • Contribute to the technical vision and roadmap of foundational AI systems

Technical scope includes foundation model training, LLM inference, similarity search, VectorDBs, Nemo Guardrails; stack includes Python/Java/Scala/Go, PyTorch, HuggingFace, AWS Ultraclusters, and cloud platforms.

The ideal candidate is a senior AI/ML engineer with 2+ years of hands-on AI production experience (or 4+ years with a Bachelor's) who can own AI services end-to-end. They should be proficient with Python/Java/Scala/Go, PyTorch, HuggingFace, and VectorDBs, and able to lead LLM-focused initiatives across multiple locations.

Bachelor's degree in Computer ScienceAIElectrical EngineeringComputer Engineeringor related fields plus at least 4 years of AI/ML experience OR Master's degree with at least 2 years AI/ML experienceAt least 4 years of experience programming with PythonGoScalaor Java
6 years of experience deploying scalable and responsible AI solutions on cloud platforms (AWSGoogle CloudAzureor equivalent private cloud)Experience designingdevelopingdeliveringand supporting AI servicesExperience developing AI/ML algorithms or technologies (e.g. LLM InferenceSimilarity Search and VectorDBsGuardrailsMemory) using PythonC++C#Javaor GolangExperience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilizationlatencythroughputand costPassion for staying abreast of the latest AI research and AI systemsand judiciously apply novel techniques in productionExcellent communication and presentation skills
AWSGoogle Cloud PlatformAzureHuggingFacePyTorchVectorDBsNemo GuardrailsPythonGoScalaJava
foundation model trainingllm inferencesimilarity searchvectordbsnemo guardrailshuggingfacepytorchpythonjavascalagoaws ultraclustersamazon web servicesobservabilityguardrailsmodel evaluationexperimentationgovernance
PythonGoScalaJavaPyTorchHuggingfaceVectorDBsNemo GuardrailsFoundation model trainingLarge Language Model inferenceLLM optimizationGuardrailsmodel evaluationobservabilityAWS UltraclustersAmazon Web Services
collaborationcommunicationproblem solvingleadershipmentoringstrategic thinkingadaptabilitydecision makingteamwork
Industry Fintech
Job Function Develop and deploy AI services for production-scale LLM workloads across Capital One locations
Role Subtype AI Engineer
Tech Domains Python, Java, Go, Scala, PyTorch, Hugging Face, VectorDBs, Nemo Guardrails, Amazon Web Services, AWS
Visa Sponsorship Yes
Lead AI EngineerAI Foundationsfoundation model trainingLLM InferenceSimilarity SearchVectorDBsNemo GuardrailsHuggingfacePyTorchPythonGoScalaJavaAWS UltraclustersAmazon Web ServicesLarge Language Model inferenceobservabilityguardrailsmodel evaluationcloud platformsML servicesHuggingFaceAWS

Less than 2 years of professional analysis experience (as per role level), Lack of Python/Java/Scala/Go proficiency, No hands-on AI/ML production experience

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