Work with me

Technical leadership and hands-on delivery for regulated industries

I work with banks, insurers, payers, payment firms and telecoms — and the software teams that serve them — where an AI agent or an enterprise system has to be explainable to an auditor as well as fast for a user. Two ways to work together, depending on whether you need a senior technical owner or a senior pair of hands inside your environment.

Choose a track ✉  Write to me
Two ways to work together

Pick the one that matches what you need

Fractional CTO

Judgment and ownership, a few days a month

Founders and leadership teams who need a senior technical owner but not a full-time hire.

  • Architecture and build-vs-buy decisions for AI and enterprise platforms, written down so they can be defended later
  • Governance for agents and retrieval: what the model may see, what it must cite, what it must decline
  • Mapping regulatory obligations to engineering work — for example CMS-0057-F prior-authorization APIs, SWIFT CBPR+ / ISO 20022 migration, DPDP Act and RBI expectations
  • Hiring, vendor selection and technical due diligence; leading delivery teams (I have led 105 engineers across ten scrum teams)

Shape: Monthly retainer with a fixed number of days. Starts with a two-week architecture and risk review.

Enquire about this

Forward-Deployed AI Engineer

Hands-on delivery inside your environment

Teams that have the use case and the data, and need an agentic system built and running in production.

  • Embedding with your team to build and ship agentic workflows against your real systems, not a sandbox copy
  • Citation-grounded retrieval with revision and regional entitlement enforced server-side
  • Streaming and integration work — Kafka, event pipelines, MCP servers over existing enterprise APIs
  • Evaluation, audit trails and runbooks, so what ships can be operated and reviewed after I leave

Shape: Fixed-term engagement, typically 8–16 weeks, scoped to a working production slice.

Enquire about this
Evidence

Things you can open and run

K-1 tax bridge

A governed bridge from tax-form data into a workflow engine, with a live demo.

Citation-grounded retrieval

Superseded revisions never reach the model; regional entitlement is enforced in the service, not trusted to the caller.

Source code

Reference implementations — Kafka on Ansible, an Embabel triage agent, a real-time voice pipeline, MongoDB benchmarks.

Notes

Write-ups of what was built, measured and got wrong.
How we start

A first conversation, not a pitch

  1. Send a short note: what the system does, what the regulator or auditor cares about, and what is slow or fragile.
  2. I reply with an honest read on whether this is a fit and which track suits it — usually within two working days.
  3. If yes, a 30-minute call, then a written scope. No scope, no start.

Tell me which track fits

Not sure? Say so — the first note can be two paragraphs. Based in Chennai; I work with teams across India, Europe and the US.

✉  yuvarajaravindan@ai-agentic-enterprises.com in  LinkedIn