Available for selected roles / Liverpool, UK / MSc Data Science & AI
I design and ship production LLM applications, retrieval pipelines and agent products, end to end — from evaluation and backend architecture to interfaces people can trust.
Three systems that show how I think: grounded answers, safer agent memory, and knowledge interfaces that make complex data usable.
An evidence-backed workspace for asking one question across multiple work sources. Every supported claim opens back to the exact record behind it, so the answer is inspectable instead of merely confident.
A memory-integrity layer that checks retrieved context before an agent acts. It surfaces suspicious provenance, blocks unsafe execution and produces a signed integrity certificate for review.
A personal knowledge system that turns uploaded material into grounded answers and a navigable 3D relationship map. It makes the source landscape visible instead of hiding retrieval behind a chat box.
I am an AI systems engineer and MSc Advanced Data Science & AI student at the University of Liverpool.
I work across the full product path: retrieval and evaluation, model orchestration, APIs, data, deployment and the interface that exposes the evidence. The goal is not an impressive prompt. It is a system that behaves clearly when the input is messy, a dependency fails or a user asks “why?”
I am currently open to UK part-time AI/software roles and internships, plus graduate opportunities from 2027.
Trace outputs to sources, evaluations or observable system state.
Make fallbacks, limits and uncertainty visible before they become incidents.
Architecture and interface are one product, not two separate demos.
Two separate authorised engagements against HydraDB. One placed top 3 in a competitive hack; the second was a structured owned-tenant assessment. Reported through coordinated disclosure; sensitive specifics withheld.
Round 01 · Hackathon Top 3 of 20+
Found an authentication / credential-handling weakness reachable without proper authorisation. Placed in the top 3 of a field of 20-plus.
Technical specifics, payloads, and affected endpoints withheld under responsible disclosure.
Round 02 · Bug bash 6 defects
Authorised read-only assessment of an owned tenant. Filed 6 reproducible defects across reliability, input validation, and API-contract correctness. Tenant isolation held throughout, with no data exposure; the core security proved sound.
Defect detail shared privately with the maintainers.
Won with QueueProof, an evidence-backed cross-source retrieval workspace where every claim opens back to its source record.
See the build →Won the Build Blitz with HydraSentry, a graph-native context-integrity harness on HydraDB.
See the build →Reached the finals with Qyntra, a self-organising wiki, built solo in roughly a day.
See the build →Entered DelOS, a delegation operating layer for coordinating multiple agents under load.
See the build →The corrected version 2 presents the architecture and analytical latency model without claiming prototype or gameplay-corpus results. It also repairs the citation error documented after v1.
Corrected v2 · Original v1 DOI archived
University of Liverpool, UK
Christ University, Bengaluru
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Open to UK part-time AI/software roles and internships, plus graduate opportunities from 2027. Fastest reply is email or LinkedIn.