Consulting
I help enterprises turn AI and cloud ambitions into production systems that actually ship. As an AI Architect and forward-deployed engineer, I embed with your teams — translating business goals into scalable architectures, building multi-agent AI and distributed backends end-to-end, and carrying them through to production and client-facing delivery.
Seven-plus years across FinTech, Open Banking, Telecom, Energy, and Industrial IoT, as a client-facing technical lead for 15+ enterprise engagements in 5 countries — much of it through Google Cloud Premier Partners and direct delivery.
What I help with
Engagements are scoped to outcomes, not hours — I optimize for the problem getting solved, measurably, and for your team being able to run what we build after I leave.
AI & Solution Architecture
Designing production-grade agentic AI and distributed-systems architectures — translating business requirements into scalable, observable, governed designs on GCP, AWS, or Azure.
GenAI Platform Design
Grounded LLM systems done right: retrieval-augmented generation over your data, evaluation and guardrails, model routing and cost control, and the infrastructure to serve it reliably.
Multi-Agent System Delivery
Building multi-agent systems on the Microsoft Agent Framework, LangGraph, Google ADK, and MCP — from orchestration patterns to durable execution and human-in-the-loop.
Cloud Migration & FinOps
Migrations and cost optimization that pay for themselves — the Tata BigQuery FinOps engagement delivered a 57% data-warehouse cost reduction; the Spanner migration tooling cut post-migration query cost materially.
Forward-Deployed Delivery
Embedding between your business and delivery teams as a technical SPOC — accelerating onboarding and deployments, resolving P1s, and setting architecture standards. See how I think about forward-deployed engineering.
Open-Source Upstreaming
Hardening and upstreaming into the frameworks you depend on — including 200+ merged contributions to Microsoft's official Go Agent Framework and core contributions to Google's Spanner Migration Tool.
Industries
Domain depth matters most in regulated and high-throughput environments, where I've delivered repeatedly:
Who I've worked with
- UK critical national infrastructure — production agentic AI for NESO (National Energy System Operator), via ClearRoute.
- Fortune 500 & large enterprise — Tata Group (57% BigQuery cost cut, ₹100 Cr+ saved), Globe Telecom (30K+ TPS transaction engine), Dainik Bhaskar (GCP-native content delivery at scale).
- Tier-1 regulated banks — Standard Chartered, via SC Ventures (Bloom secure cloud provisioning, SOC 2 / ISO 27001).
- UAE / Saudi regulated FinTech — Bancnet Open Banking platform (ADGM / DIFC / SAMA), with data residency and consent management.
- Global telco vendors — Ericsson and AT&T (Kubernetes-native cloud lifecycle, azure-service-operator and airshipit).
How I work
My default model is forward-deployed: I embed with your team, learn the real problem (not just the stated one), build the thinnest thing that proves value, then harden it into production and hand it over so you own it. I optimize for the customer's outcome over the cleverness of the solution — a modest system that is trusted, measured, and actually used beats an impressive one that stalls in a pilot.
I bring the full lifecycle: discovery and architecture, hands-on build in Go and Python, evaluation and guardrails for AI systems, security and governance, and the client-facing communication to keep stakeholders aligned. You can read how I think about this in the AI Forward Deployed Engineer and Forward Deployed Engineering series.
Let's talk
If you're turning an AI or cloud ambition into something that has to work in production, I'd like to hear about it. Reach out and we'll figure out whether I'm the right fit.