Jason Layton

Senior AI Engineer with 9+ years of experience designing and deploying production-grade AI solutions across finance, healthcare, and retail industries. Proven success delivering LLM platforms, multi-agent systems, RAG pipelines, and scalable cloud-native applications on Azure and AWS. Strong background in Python, distributed systems, APIs, and enterprise architecture. Known for improving operational efficiency, reducing latency, and delivering measurable business impact.

Senior AI Engineer at Jefferies (2023-09 – 2025-12)

• Architected enterprise multi-agent AI platform using Azure AI Foundry and Azure OpenAI for financial analytics and automated reporting.
• Built RAG pipelines using Azure AI Search and pgvector to retrieve insights from large financial datasets.
• Integrated MCP servers and tool-calling workflows to connect AI agents with internal systems securely.
• Implemented monitoring, identity controls, and governance using Azure Monitor and Azure AD.
• Reduced inference latency by 35%, improving analyst productivity and response speed.

AI Engineer at Johnson & Johnson (2021-11 – 2023-08)

• Developed HIPAA-compliant AI solutions using Amazon Bedrock, SageMaker, and AWS Lex.
• Designed hybrid search platform with OpenSearch across patient and clinical records.
• Automated onboarding workflows using AWS Lambda and Step Functions.
• Improved patient onboarding efficiency by 40%.
• Enhanced compliance, data privacy, and operational scalability.

Software Engineer at Badger Technologies (2019-08 – 2021-10)

• Improved AI recommendation platform with LLM-powered personalization and shopping assistant features.
• Developed real-time data pipelines using Python, SQL, Spark, and AWS Kinesis.
• Implemented vector database search pipelines for faster product retrieval.
• Increased recommendation accuracy by 28%.

Software Engineer at HCLTech (2017-08 – 2019-07)

• Built enterprise web and distributed applications using.NET, Node.js, and microservices architecture.
• Designed API gateway solutions and RabbitMQ messaging systems.
• Created CI/CD pipelines using Docker, Kubernetes, Jenkins, and AWS.
• Improved application performance by 25%.

Bachelor of degree – Arizona State University (2013 – 2017)