Enterprise Backend Consultant & AI Engineer | 20+ Years Experience | Java, Spring, Node.js, AWS, AI

Summary

Enterprise Backend Consultant and AI Engineer with 20+ years of experience delivering resilient, high-throughput distributed systems across capital markets, global aviation, banking and government. Combining technical leadership with hands-on delivery: resolving complex architectural and performance challenges, modernising legacy platforms, and delivering production-grade cloud applications.

Now extending this enterprise engineering discipline into Generative AI, building production-oriented agentic systems with LangGraph, multi-model orchestration, evaluation-driven testing and Spring-based RAG, with a focus on reliability, testability and maintainability.

Core strengths

• System design: distributed systems, microservices, event-driven architecture and REST APIs built for scale and resilience
• Performance and modernisation: tuning large legacy platforms and migrating them to modern runtimes
• Data streaming: Kafka, Debezium and Apache Iceberg pipelines, including a firm-wide Data Mesh
• Applied GenAI: agentic workflows, RAG, model routing, LLM evals and guardrails, built to production standard
• Engineering quality: TDD, automated testing, CI/CD and infrastructure as code
• Leadership: leading delivery for enterprise clients and mentoring engineers by example

Recent AI engineering

Self-directed programme building production-grade GenAI systems; all code is public on GitHub.

• Quantum Sage: AI-assisted trading signal engine that turns an analyst's market notes into structured, tradeable signals (Node.js/TypeScript, LangChain, LangGraph). Promptfoo eval regression tests, safety guardrails, CI and Docker, built spec-first with OpenSpec.
• Monty: multi-model LLM pipeline in LangGraph.js with a prompt-injection guardrail, parallel X (Twitter) sentiment search and a Java 25 signals service, then DeepSeek synthesis. Routing model chosen with an eval harness (29/30 vs 25-27/30, zero missed searches); synthesis cost cut roughly 45x at comparable quality.
• AI Market Intelligence Platform: Spring Boot RAG backend with pgvector embeddings, cost controls and prompt governance.

Selected experience

• MarketAxess: built the firm's Data Mesh ingestion pipeline (Java 17, Kafka Streams, Debezium, Iceberg), reducing onboarding for new data producers to a simple formality
• Amadeus: improved performance of Cytric, a travel platform spanning 1,000+ Oracle tables, migrated a legacy service to Quarkus, and shipped to OpenShift on Microsoft Azure
• Boyle Software: led delivery for DBS Bank, Vroom and Kinship; halved Spark ingestion runtime for DBS Bank and mentored the Vroom team
• TokenPass: led engineering for a SaaS platform that hid blockchain complexity from non-technical users, and cut running costs by replacing a third-party backend
• London School of Economics: sole engineer on the course search platform, delivered four weeks early
• International assignments: 15+ enterprise systems across four continents, including the French Ministry of the Interior's national emergency alert backend and a mobile banking portal for Capitec Bank

Technical toolkit

• Backend: Java, Spring Boot, Quarkus, Node.js/TypeScript, Go
• Data: Kafka, Spark, PostgreSQL, Oracle, Redis, Elasticsearch
• Cloud: AWS, Microsoft Azure, GCP, Kubernetes, OpenShift, Terraform
• GenAI: LangChain, LangGraph, Spring AI, MCP, AWS Bedrock, OpenRouter, Promptfoo

Credentials and availability

• AWS Certified Solutions Architect and Developer (Associate)
• BSc (Hons) Computer Systems, University of Limerick
• Irish (EU) citizen, available immediately, open to relocation or remote work