Atlanta Metropolitan Area
II'm a software engineer who builds enterprise systems and agentic AI tools end to end. The part I care about most is never the demo. It's the trust layer. Most recently I built jobContextMCP, an open-source Model Context Protocol server that gives AI assistants persistent memory over a job search: career history, interview notes, writing samples, GitHub metrics, and application pipeline. It runs 77 tools and 923 passing tests, with a RAG layer over a career corpus, LangGraph agent workflows, local and cloud LLM support, and a mobile share-sheet that drops job postings straight into the pipeline from my phone. It started as a tool for me. It's now a multi-tenant platform on Azure AKS with per-user data isolation and Entra ID auth, live at jobcontext.ai, which meant rebuilding it to hold other people's data without ever leaking mine into it. Here's the bug I'm proudest of fixing. One of the LangGraph resume-review pipelines started inventing fake metrics because its reviewer node kept demanding stronger numbers. That forced a real guardrail fix: move the no-fabrication rule into the system layer, and let the reviewer accept a named artifact when a number would be dishonest. That's the kind of failure you only find by building the thing, running it, watching it break, and fixing the architecture. Before jobContextMCP, I was a Level 6 Software Engineer at General Motors, leading cloud and database modernization across mission-critical applications. I drove zero-downtime migrations from Cloud Foundry to Azure Container Apps and from Oracle to PostgreSQL Flexible Server, built Terraform infrastructure, modernized Java/Spring Boot/Angular stacks, and mentored teams through migration work that cut implementation time by 60%+. My strongest lane is the intersection of enterprise software engineering and practical AI systems: • Agentic AI tooling, MCP servers, RAG, LangGraph, evaluation and guardrail patterns • Java, Spring Boot, Angular, TypeScript, Python, FastAPI • Azure (Container Apps, AKS), PostgreSQL, Terraform, Docker, Kubernetes, CI/CD • Enterprise modernization, authentication, cloud migration, and developer productivity • Building tools people can actually run, inspect, test, and trust I'm especially interested in applied AI, developer tools, platform engineering, backend, and full-stack roles where the work has to survive contact with real users.
Built and maintain jobContextMCP, an open-source Model Context Protocol server that gives AI assistants persistent context over a real job search workflow: pipeline tracking, fitment analysis, resume and cover-letter generation, interview prep, outreach, social metrics, GitHub traffic, and personal career story retrieval. • Built 77 MCP tools across job tracking, resume generation, interview prep, contact management, LinkedIn/social tracking, RAG search, GitHub metrics, and document export • Maintained 565 passing tests across tool, service, transport, dashboard, and workflow layers • Implemented RAG over a structured career corpus including STAR stories, resumes, interview notes, tone samples, recruiter context, and application history • Built LangGraph resume pipelines with draft/review/revise loops, persona-aware fitment analysis, and no-fabrication guardrails • Added GitHub traffic tracking that snapshots 14-day clone/view windows into durable local history; jobContextMCP saw 324 clones from 147 unique cloners in the latest tracked 14-day window • Added local and cloud LLM routing via OpenAI-compatible clients, including Ollama support for local inference • Built FastAPI/HTTP transport, dashboard views, secure remote access, and mobile share-sheet workflow for sending job postings into the pipeline from iPhone • Used the system daily in production for real applications, outreach, interview prep, and job-search tracking Technologies: Python • FastAPI • MCP • LangGraph • RAG • OpenAI API • Ollama • pytest • GitHub API • Docker • Tailscale
• Promoted to Level 6 in 2023 for technical leadership, successful project delivery, and cross-team mentorship; led dual-track migration of MADM from Cloud Foundry to Azure Container Apps and Oracle to PostgreSQL, achieving zero-downtime cutover. • Architected cloud-native infrastructure using Terraform (IaC), upgraded stack to Spring Boot 3.5.4 and Angular 18, and automated deployments via GitHub Actions, eliminating manual processes. • Published MSAL integration documentation enabling standardized OAuth2/MSAL authentication across enterprise teams; led technical seminar on Agentic AI usage demonstrating practical integration for accelerating framework upgrades. • Mentored multiple teams through OCF migrations reducing their implementation time by 60%+; as co-owner of MADM and DMR, implemented Sterling Interface replacement, created Purchase Products and Best Estimate interfaces for simultaneous uploads, and resolved long-standing BARS variance through query optimization. • Completed PCF to OCF migration for MADM, NADPA, and DSS with OAuth2 updates; achieved 100% BC compliance through DMR single-source migration and configured DataStage interface to load M-Schedule data from DPOF via API. • Performance metrics (2025): 98% SLA (P1/P2), 95% SLA (P3/P4); 98% security fitness, 95% tech fitness, 100% dead-code fitness; 10%+ AI tools integration across development. Technologies: Java • Spring Boot • Angular • TypeScript • Azure (Container Apps, PostgreSQL, Terraform) • Docker • Oracle • DataStage • GitHub Actions • MSAL • Power BI
• Single-handedly modernized legacy codebase upgrading Java, Spring Boot, and Angular across multiple releases, restoring maintainability and enabling cloud migration efforts • Designed and developed scalable backend microservices using Java and Spring Boot with event-driven architecture, integrating PostgreSQL, Oracle, Redis, and IBM DataStage for enterprise data pipelines • Maintained 80%+ test coverage using TDD principles and conducted thorough code reviews to ensure code quality, security, and performance • Resolved long-standing Azure DevOps pipeline issues, enabling continuous deployment and improving team velocity • Led Angular Developer’s Group as admin, facilitating knowledge sharing and technical discussions across the organization
• Took sole ownership of an undocumented legacy application with no working branches and drove it from Java 8, Spring Boot 2.2, and Angular 6 through multiple out-of-scope upgrade cycles while keeping production stable; this self-directed work drove promotion to Level 6. • Upgraded Java (8→11→17→21), Spring Boot (2.1→2.5→3.5.4), and Angular (6→14→16→18) across MADM and related applications; resolved Azure DevOps pipeline failures that had blocked releases since 2021. • Implemented multiload functionality for MADM UI enabling simultaneous file processing; assisted DSS team with Java/Spring Boot upgrades, demonstrating cross-team collaboration. • Validated Hadoop to Greenplum migration and built ETL pipelines, PySpark scripts, and DDL for multi-source data integration; developed automated monitoring framework for ETL jobs improving troubleshooting and data reliability. • Configured table loads with HQL queries, Autosys configurations, and Greenplum loads; maintained 80%+ unit test coverage across 500K+ line codebase with DevOps quality gates and automated post-deployment testing. • Facilitated Java training for New Career Hires improving team onboarding; maintained comprehensive wiki documentation for knowledge transfer. Technologies: Java • Spring Boot • Angular • Python • Spark SQL • Greenplum • Apache Hive • Autosys • Azure DevOps • Git
• Diagnosed complex hardware and software issues for a high volume of customers, translating technical findings into clear, non‑technical guidance. • Partnered with cross‑functional store teams to surface recurring failure patterns and improve the customer resolution process.
•Created improved beer menu using experience and research to create a menu that is both adventurous and access •Managed repairs and maintenance of bar facilities and kept weekly FIFO logs •Maintained goal cost percentages through training and accountability •Increased alcohol sales from 5 % of revenue to over 25 %