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ActiveDublin, IrelandAI Engineer — Agents, Evals, Guardrails

ANURAGNIMONKAR

Pressure is a skill.

I build agent systems — and the harnesses that prove they work.

Tale of the tape

Patents

2

1 pending · first 18 months

Sev-1 record

2–0

resolved <12h and <4h

Eval conversation success

77–86%

from 30–40% · LLM user-simulator rebuild

CI pipeline

~30s

from 10–15 min · record/replay proxy

API spend removed

$35–70K/yr

LLM-call scoring replaced with local compute

Stack owned

runtime → evals → RAG

end to end

Main card

Main event

Agent Policy Layer

Python · protocol design · CI/CodeQL

Built an open-source guardrails protocol that enforces agent policies at the call site — runtime-agnostic, fail-closed by default, one line to instrument.

Co-main

Banco do Brasil — agent migration

Multi-agent systems · Tekton · production ownership

Led a squad migrating a bank's PIX, Cards, and Accounts agents, and resolved two production Sev-1s under load — one by re-architecting an execution graph, one with an idempotent single-writer registration toolkit.

Featured

The eval rebuild

LLM evaluation · proxy caching · patent-pending

Rebuilt an agent evaluation stack — an LLM user-simulator, a record/replay proxy, and a local semantic analyzer — moving conversation success from 30–40% to 77–86% while cutting run cost and time.

Prelims

  • RAG migration off Milvus0 regressions
  • agentevaluatoropen-source · Claude Skill
  • PION GPU port · DIAS2.5× speedup
  • Heart-sound segmentationsignal research · IISc

The corner

I take longer to learn things than most people. Two to four times longer. I've stopped apologizing for it, because what comes out the other side doesn't lose.

In my corner — coffee, iron, and the long way round.