About Ed
IT engineer turned AI specialist building controlled, trustworthy AI for regulated environments. 5 years in applied AI/ML and recently production-grade AI agents that take actions with embedded guardrails, policy enforcement, and audit-ready logging. I bridge software, DevOps/MLOps, and AI assurance (testing, risk, red teaming, GRC) to ship reliable systems across cloud and edge.
English
Native or bilingual
Can work on-site
London (up to 50km)
Experience
- Industrial AI SystemsSenior AI Agent EngineerTECHSeptember 2024 - Today (1 year and 9 months)London, United Kingdom
- Built and deployed AI Agents for operations and maintenance workflows where agents can take real actions (ticketing, configuration changes, edge device commands) under strict controls.
- Designed an agent runtime with embedded guardrails: role-based permissions, policy checks, action simulators, and approval gates for high-impact operations.
- Integrated agents with edge/controls systems (OPC UA / MQTT patterns), enabling safe execution of diagnostics and parameter recommendations with constraint enforcement.
- Implemented deterministic control wrappers around LLM decisions (state machine + constraint solver), reducing unsafe actions and improving reliability in production.
- Developed evaluation suite: scenario-based tests, tool-call validation, hallucination detection, and regression checks for every model/prompt change.
- Added observability: structured traces of agent reasoning steps, tool usage, latency breakdown, and audit trails for compliance.
Key outcomes: improved incident triage time, increased first-time-fix rate for common faults, and reduced operator workload through controlled automation. - TechOps AnalyticsAI / ML EngineerTECHJanuary 2021 - June 2024 (3 years and 5 months)London, United KingdomDelivered ML solutions across forecasting, anomaly detection, and NLP automation for IT operations and customer support.
- Built anomaly detection for infrastructure metrics and logs; reduced alert noise and improved detection of early failures.
- Developed NLP pipelines for ticket categorisation, routing, and summarisation; improved SLA adherence through faster triage.
- Productionised models with CI/CD, monitoring, and drift detection; partnered with SRE to define reliability targets.
- Implemented RAG-based assistants for internal knowledge search with access controls and secure data handling.
- Global Services GroupIT Engineer / Systems EngineerTECHJune 2016 - December 2020 (4 years and 6 months)London, United KingdomOwned infrastructure reliability, automation, and secure operations across on-prem and cloud environments.
- Led migration of core services to cloud; improved availability and reduced deployment risk via infrastructure-as-code.
- Automated patching and configuration management; improved compliance and reduced manual workload.
- Built monitoring/alerting strategy and incident response playbooks; reduced MTTR through better observability.
- Supported networking, identity management, and endpoint hardening in collaboration with security teams.
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Education
- BSc Computer ScienceUniversity of Manchester2026