Jay P.

About Jay P.

Software Engineer with 9+ years of experience building scalable backend systems, cloud-native applications, and enterprise APIs. I specialize in Python development, microservices architecture, and high-performance API platforms using frameworks such as FastAPI and Django.Currently at Apple, I work on AI and LLM integrations, building production-grade agentic applications that enable AI systems to safely interact with enterprise services and workflows. My work focuses on designing structured tool interfaces, implementing strong security and validation layers, and developing observable services with robust logging, monitoring, and scalable containerized deployments.Throughout my career, I have delivered high-impact backend platforms across healthcare, government, and enterprise retail systems, helping teams build reliable systems that support high-volume transactions and mission-critical workloads.Key impact highlights:• Improved API response performance by 30–45% through database query optimization and asynchronous processing in FastAPI• Reduced production debugging and incident resolution time by ~40% by implementing structured logging and centralized monitoring with Splunk, Grafana, and CloudWatch• Increased deployment efficiency by 60–70% by implementing CI/CD pipelines with Jenkins and GitHub Actions for automated builds and Kubernetes deployments• Improved system scalability to handle 2–3x higher concurrent workloads through Docker containerization and Kubernetes orchestration• Simplified AI tool architecture by consolidating 28 LLM tools into 7 MCP tools, reducing integration complexity by ~75%• Reduced API integration failures by ~35% through JSON schema validation, versioned APIs, and strict contract enforcementTechnical Focus:• Python (FastAPI, Django) backend development• AI/LLM integrations and MCP tool development• Microservices architecture and REST API design• Cloud-native deployments using Docker, Kubernetes, and AWS• CI/CD automation and DevOps practices• Database design and query optimization (PostgreSQL, Oracle, MySQL)• Observability with structured logging, monitoring, and alertingI’m passionate about bridging AI capabilities with real-world enterprise systems through secure, scalable, and well-documented APIs.Outside of engineering, I’m a marathon runner who has completed 6 marathons so far, with a personal goal of running one marathon every month in 2026. I also enjoy hiking and spending time in nature.Always open to conversations around AI infrastructure, backend engineering, and distributed systems.

Experience

1. Agentic Ai Software Developer

   Apple

   Jan 2025 — Present · Austin, TX, US

   Designed and developed a production-ready MCP server in Python enabling LLM clients to manage the full meeting lifecycle over CalDAV, consolidating 28 tools into 7 action-based tools to improve maintainability and efficiency-> Built RESTful APIs and tool interfaces using FastAPI, implementing consistent JSON-based request/response contracts, schema validation, and reliable interaction with LLM agents-> Implemented structured logging integrated with Splunk for centralized monitoring, operational analytics, and improved debugging of production systems-> Applied security-first design principles, enforcing CommandInjectionGuard pre/post checks on all MCP tools and sanitizing all user inputs to prevent injection vulnerabilities-> Maintained comprehensive technical documentation (TOOLS_REFERENCE, ARCHITECTURE, SECURITY, LOGGING) and ensured documentation accuracy through PR review policies-> Conducted end-to-end testing of MCP tools using Enchante and Endor MCP clients, validating tool discovery, request execution, and response formatting across meeting lifecycle APIs-> Verified MCP protocol compatibility through MCP Inspector by testing tool registration, parameter validation, and structured JSON response compliance-> Containerized the MCP server using Docker with multi-stage builds to optimize image size and separate build-time and runtime dependencies-> Deployed and managed containerized applications using Docker and Kubernetes for scalable and reliable environments-> Used GitHub for version control and Jenkins for CI/CD pipelines, supporting automated builds, testing, and deployment workflows.

Education

• San Francisco Bay University

  Master's degree, Computer Science

Skills

• Sql
• Hibernate
• Soap
• Representational State Transfer (Rest)
• Json
• Amazon Web Services (Aws)
• Junit
• Spring Framework
• Github
• Ajax
• Oracle Database
• Weblogic
• Pl/Sql
• Javascript
• Log4j
• Mysql
• Spring Mvc
• Maven
• Sas
• Agile Methodologies
• Toad
• C
• Splunk
• Tomcat
• Machine Learning
• Java Database Connectivity (Jdbc)
• Rstudio
• Jerseys
• Web Services
• Xml
• Map-Reduce
• Java
• Hadoop
• Angularjs
• Javaserver Pages (Jsp)
• Jenkins
• Html
• Microsoft Office