✦ Luna Orbit — AI & Machine Learning

Sr. Distinguished AI Engineer

at Capital One Financial

📍 6 Locations Unknown 💰 $314K – $359K USD / year Posted April 14, 2026
Salary $314K – $359K USD / year
Type Not Specified
Experience executive
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

Senior Distinguished AI Engineer role focused on building and deploying AI software components across the Intelligent Foundations and Experiences (IFX) team. The position emphasizes production LLM capabilities, including guardrails, evaluation, experimentation, governance, and observability, plus LLM optimization for scalability, cost, latency, and throughput.

  • Develop and deploy AI software components (foundation model training, LLM inference)
  • Implement similarity search, guardrails, evaluation, experimentation, governance, and observability
  • Leverage AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch
  • Invent LLM optimization techniques to improve scalability, cost, latency, and throughput
  • Partner with cross-functional teams to deliver AI-powered products

Designs, develops, tests, deploys, and supports AI components such as foundation model training and large language model inference, along with similarity search and guardrails. Works with Open Source and SaaS AI technologies including AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch, and applies state-of-the-art LLM optimization techniques for large-scale production systems.

The ideal candidate is a senior AI engineer focused on production LLM systems with deep experience in foundation model training and large language model inference. They have hands-on ability to implement guardrails, model evaluation, experimentation, governance, and observability, and they optimize large-scale AI for scalability, cost, latency, and throughput. They are proficient with AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch and can partner effectively with cross-functional teams to deliver AI-powered products.

Designdeveloptestdeployand support AI software components including foundation model traininglarge language model inferencesimilarity searchguardrailsmodel evaluationexperimentationgovernanceobservabilityLeverage Open Source and SaaS AI technologies such as AWS UltraclustersHuggingfaceVectorDBsNemo GuardrailsPyTorchInvent and introduce state-of-the-art LLM optimization techniques to improve performance - scalabilitycostlatencythroughput - of large scale production AI systemsPartner with a cross-functional team of engineersresearch scientiststechnical program managersand product managers
AWS UltraclustersHuggingfaceVectorDBsNemo GuardrailsPyTorch
foundation model traininglarge language model inferencesimilarity searchguardrailsmodel evaluationexperimentationgovernanceobservabilityAWS UltraclustersHuggingfaceVectorDBsNemo GuardrailsPyTorchLLM optimization techniquesscalabilitycostlatencythroughputresponsible and reliable AI systems
AI software componentsfoundation model traininglarge language model inferencesimilarity searchguardrailsmodel evaluationexperimentationgovernanceobservabilityOpen Source AI technologiesSaaS AI technologiesAWS UltraclustersHuggingfaceVectorDBsNemo GuardrailsPyTorchLLM optimization techniquesscalabilitycostlatencythroughputproduction AI systemsresponsible AIreliable AI systemsmachine learning
cross-functional collaborationtechnical vision and roadmap contributionstaying abreast of latest researchability to understand scientific publicationsapply novel techniques in productioncommunication
Industry Banking
Job Function Build and optimize production LLM systems with responsible AI controls
Role Subtype LLM Engineer
Tech Domains Amazon Web Services, Python
Sr. Distinguished AI EngineerDistinguished AI EngineerAI engineermachine learningresponsible and reliable AI systemsfoundation model traininglarge language model inferencesimilarity searchguardrailsNemo Guardrailsmodel evaluationexperimentationgovernanceobservabilityOpen SourceSaaSAWS UltraclustersHuggingfaceVectorDBsPyTorchLLM optimization techniquesscalabilitycostlatencythroughputproduction AI systemsIntelligent Foundations and Experiences (IFX)

Hands-on experience with foundation model training and large language model inference, Ability to implement guardrails and conduct model evaluation and experimentation, Experience leveraging AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch, Experience inventing LLM optimization techniques for production systems

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