Graham Anderson
Evergreen, CO · gramman87@gmail.com · grahamanderson.dev · linkedin.com/in/graham-anderson-denver
Based in Evergreen, CO · open to relocation
Summary
Full-stack software engineer who builds production features across the whole stack, JVM/Spring Boot services, APIs, and data models on the backend, TypeScript and React on the front end. Ships agentic AI applications on Claude in Python and TypeScript: MCP servers (producer and consumer), tool-calling agents, sub-agent orchestration, RAG, and real-time streaming. Modernizes legacy enterprise systems and deploys them onto AWS, OpenShift, and Kubernetes through CI/CD pipelines. Acts as Scrum Master for a 5-person engineering team at Accenture Federal Services, coordinating with partner teams and reporting progress and risks up the chain to leadership. Takes pride in well-tested, maintainable code and sound API governance: versioning, backward compatibility, and security on public-facing surfaces.
Core Strengths
- ·Backend (JVM): Java, Spring Boot, REST APIs, modular monolith architecture, service decomposition design, OpenAI-compatible endpoints, systems integration, SQL
- ·Frontend: TypeScript, React, Next.js, Angular/AngularJS, HTML/CSS, Tailwind, data visualization
- ·AI & Agentic: Claude API, tool & function calling, MCP (producer + consumer), agents and sub-agents, real-time streaming (SSE/WebSockets), RAG, evaluation harnesses
- ·Testing & Quality: JUnit, Claude-as-judge evaluations, evaluation harnesses; API governance: versioning, backward compatibility, security standards
- ·Cloud & DevOps: AWS, Kubernetes, OpenShift (OCP), Docker, GitLab CI/CD, HashiCorp Vault, containerized deployment
- ·Delivery: Python, Agile/Scrum, cross-functional collaboration, release planning, $80M+ program leadership
Professional Experience
- ·Modernize a government off-the-shelf (GOTS) application, migrating its stack onto Red Hat OpenShift (OCP) to shorten feature release cycles; containerized its multi-component Java/Spring Boot monolith and deployed it through CI/CD.
- ·Cut deployment time 40% by parallelizing and caching GitLab CI/CD pipelines, shortening the loop from code change to deployable build.
- ·Act as Scrum Master for a 5-person engineering team: run Agile ceremonies, coordinate dependencies with partner teams, and report progress and risks up the chain to leadership.
- ·Build full-stack features from REST APIs to AngularJS front ends, holding to versioning, backward-compatibility, and security standards on public-facing APIs.
- ·Centralized application secrets in HashiCorp Vault to meet federal compliance requirements.
- ·Built Java features with SmartGWT/JavaScript front ends for a DCIM (data center infrastructure management) platform used by hyperscale operators to manage their infrastructure.
- ·Authored and consumed REST APIs for real-time device communication and integration with customers' enterprise systems.
- ·Streamlined deployment workflows by optimizing integration scripts, reducing manual handoffs between releases.
- ·Built full-stack applications in Java, Spring Boot, Angular, and JavaScript deployed on AWS with RESTful service architectures.
- ·Served as Scrum Master and Database Administrator, enforcing Agile cadence, facilitating ceremonies, and driving robust schema design.
- ·Led pre-construction on 15 to 20 bids a year ranging from $5M to $85M, winning roughly 1 in 4, and owned scope development, estimating, business cases, procurement strategy, and risk evaluation before mobilization.
- ·Trained junior estimators, superintendents, and new project managers, building the bench that carried projects from bid to field.
- ·Coordinated procurement, engineering, manpower, and scheduling into a delivery plan for each awarded project.
Agentic AI Engineering: Independent Work
- ·Spring Boot MCP Agent (github.com/Gramman87/spring-mcp-agent): a full-stack Java 21 / Spring Boot service that publishes tools over an MCP producer surface and runs a streaming agent consuming them over SSE, fronted by a React/TypeScript UI, with an OpenAI-compatible endpoint and a JUnit suite covering tools, registry, agent logic, and controllers. The LLM seam is isolated so a real Claude tool-use call drops straight in.
- ·Ship full-stack applications on the Claude API: MCP servers as both producer and consumer (stdio + Streamable HTTP transports), tool-calling agents, sub-agent orchestration, RAG pipelines, and real-time streaming UIs in Python and TypeScript/React. Every project is live and open-source.
- ·Stand up evaluation harnesses, including Claude-as-judge scoring on routing correctness, coverage, and output quality across hand-written cases, to iterate prompts and tool definitions and catch regressions.
- ·Hands-on with agentic coding tools (Claude Code, Cursor) and LLM integration patterns: tool/function calling, OpenAI-compatible endpoints, data streaming, and the Model Context Protocol as a producer and consumer.
Education
- ·Skill Distillery: Certificate, Full Stack Java Development (2021–2022)
- ·Metropolitan State University of Denver: Computer Science coursework