Build the intelligence
Evidence-grounded RAG, structured model outputs, semantic retrieval and Python APIs. Systems designed to make AI responses useful and traceable.
AI ENGINEER & SOLUTIONS ARCHITECT
Open to AI opportunitiesAI, engineered
for the real world.
I turn complex ideas into grounded AI systems.
Hands-on engineering, enterprise architecture and the judgement to connect them.
GROUNDING · ORCHESTRATION · EVALUATIONThe experience behind the engineering
01 / WHAT I BRING
The AI capability.
The production mindset.
Modern AI needs more than a model. It needs someone who can build the system around it.
My background spans financial services, healthcare and cloud platforms. Today, I apply that experience to LLM applications, retrieval systems and AI products: connecting engineering detail with architecture and business priorities.
I bring hands-on Python and AI delivery alongside years of accountability for resilience, security, change control and operational support.
Engineer the platform
Connect AI to application data, services and delivery workflows. Bring evaluation, observability and cloud architecture into the design from the start.
Lead the delivery
Translate a business problem into architecture, a practical roadmap and an engineering plan. Lead technical conversations and stay close to implementation.
02 / SELECTED WORK
From thinking
to working systems.
Applied research, product engineering
and purposeful AI architecture.
FACTR.
From spoken claims
to traceable evidence.
An end-to-end AI system that takes media through transcription, claim extraction, semantic retrieval and structured verdict generation.
I designed and built the Python pipeline, connecting speech processing, LLMs and a domain knowledge base with citation and confidence outputs.
Explore the engineering
The challenge
Turn unstructured media into claims that can be checked against an explicit evidence base.
The implementation
Combine transcription, LLM claim extraction, embeddings and vector retrieval with evidence matching and structured outputs.
The engineering evidence
Implemented grounding controls, citation and confidence outputs, plus quantitative retrieval evaluation using Precision@k, Recall@k and mAP.
The qualification
Developed as my University of Hull MSc Artificial Intelligence dissertation project; MSc awarded Distinction in 2026.
FACTR / SYSTEM ARCHITECTUREPipeline overview
Evidence at every step.
- 01Media → transcriptINPUT
Speech recognition with Whisper
- 02Extract the claimsPARSE
LLM extraction · structured outputs
- 03Retrieve the evidenceGROUND
Embeddings · FAISS · domain knowledge
- 04Generate a verdictVERIFY
Evidence matching · citations · confidence
Evaluate the retrieval
Precision@k · Recall@k · mAP
UniNexus.
Intelligent learning.
Meaningful career connections.
CEO, co-founder and hands-on AI engineering lead for a platform connecting students, universities and industry through AI tutoring, knowledge discovery and career intelligence.
My contribution
Define the AI architecture and product roadmap, contribute to workflows and API integration, and coordinate three engineers and AI specialists.
Lead technical validation across AI services, backend APIs and front-end integrations, with testing and release quality gates. The programme spans MVP development and production-readiness work.
DonateDirect.
Designing trust into
charitable giving.
AI verification architecture for charity workflows, connecting multimodal validation concepts, milestone checks and traceable decisions with secure transaction design.
Explore the design
Designed image-text verification concepts, milestone validation, identity integration and audit trails for a pre-production charity platform.
The architectural focus is a clear chain between evidence, review and transaction flow, with human oversight where needed.
03 / ENTERPRISE EXPERIENCE
New technology.
Seasoned judgement.
UniNexus
CEO & Co-Founder / AI Engineering & Platform Lead
Technical leadership and hands-on AI product delivery: architecture, retrieval workflows, API integration, engineering coordination and release readiness.
Invesco
Principal Engineer / Design Authority · Cloud & Platform
Engineered, audited and performance-tuned global hybrid platforms across US, EMEA and APAC. Scope included 14K+ server and Citrix workloads, VMware estates and approximately 12.5 PB of NetApp storage.
Worked across AWS services, automation, resilience, security and architecture governance in a regulated financial-services environment.
NHS, Betfair & consulting
Systems development, cloud architecture & operations
Five years as Haemophilia Systems & Development Manager at Guy’s & St Thomas’ NHS, leading a four-person development team supporting live patient services.
Further cloud and platform roles at Frimley Park Hospital, Betfair, Semafone and Cloudmotion built a foundation in software delivery, secure platforms and operational reliability.
ALWAYS BUILDING
Depth from experience.
Momentum from curiosity.
Alongside product delivery, I build and test agentic workflows with LangGraph, LangChain and MCP, and explore cloud AI through Azure AI Foundry and AI Search, AWS Bedrock, and Google ADK / Vertex AI labs.
That practical learning extends my enterprise background into stateful agents, tool use, human oversight and cloud AI deployment patterns.
ACADEMIC FOUNDATIONMSc Artificial Intelligence · Distinction
University of Hull · 2026
04 / THINKING IN PUBLIC
Engineering perspectives.
AGENT JUNKY / LINKEDIN
Speed, control and governance in agent platforms.
Choosing frameworks around the problem, the constraints and the trade-offs.
Read the post AI SYSTEMS / LINKEDINBuilding an AI agent: a seven-step process.
From prompts and tools to orchestration, interfaces and evaluation.
Read the postLET’S BUILD SOMETHING THAT MATTERS
UK · Remote · International opportunitiesYour next AI challenge.
Let’s talk.
I’m exploring Senior AI Engineer, AI Solutions Architect and AI technical leadership roles where hands-on delivery and enterprise experience can make a difference.
Discuss an opportunity +44 7904 278139LV@Coachstate.online