amogh@sf:~$ whoami

Forward Deployed Engineer_

> founding FDE @ MoolAI
> taking enterprise AI agents from pilot to production
> multi-agent systems · LLM evaluation · context engineering

// impact.log

Results from real enterprise deployments

Agent systems I've shipped for paying customers in finance, supply chain, and security.
Enterprise EPM financial review cycle, via a hierarchical multi-agent system
Security alert triage in an air-gapped deployment, at 99.9% uptime
Logistics reconciliation across disconnected supply-chain systems
Running Slack & Microsoft Teams agents in production on their EPM, ERP, and accounting data
// what_i_do

Taking AI agents from pilot to production

I sit between the customer and the platform. I scope the problem with the customer's team, build the agent system, and ship it to production with guardrails.

Hierarchical & ReAct-style orchestration

Multi-Agent Systems

Supervisor/sub-agent systems built with LangGraph and MCP, running in production for EPM, healthcare, and network-security customers, including air-gapped on-prem environments.
2 provisional patents

LLM Evaluation & Context Engineering

Architect of Judge Council (LLM-as-a-Judge evaluation) and ContextForge (declarative RAG/CAG context engineering), two core MoolAI platform components.
Pilot to production, reproducibly

Agent Deployment & Infrastructure

Terraform-driven agent deployments across customer-tenant and managed Azure, plus Kubernetes and on-prem work on AWS, GCP, and edge hardware.
Where it started

Data Engineering Roots

Two years at LTIMindtree building PySpark, Kafka, and Delta Lake pipelines that processed 2TB+ of data a day. That's where the production mindset I bring to AI systems comes from.
// git log --career

From data pipelines to production AI agents

2025 → now

Founding FDE · MoolAI

Engineer #3. I build the agent platform (two provisional patents) and lead delivery for enterprise customers from scoping through go-live.
2023 → 2025

M.S. Analytics · SF State

Graduate research on FogBrain, private LLM inference on a Raspberry Pi edge cluster. Runner-up in the CSU Business Analytics Competition 2024.
2021 → 2023

Data Engineer · LTIMindtree

Streaming and lakehouse pipelines on Databricks, Kafka, and Azure DevOps. Processed 2TB+ of IoT data a day and cut ETL from 7 days to 2.
2017 → 2021

B.E. Computer Science · VTU

Visvesvaraya Technological University, Bengaluru. Co-authored a published paper on currency authentication with image processing and k-NN.

© 2026 Amogh Ranganathaiah · built with coffee and curiosity · exit 0

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