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Ali Khatami

Technical Product Leader · Staff-Level Platform Engineer

aliikhatami94@gmail.com·New York, NY·linkedin.com/in/akhatami·github.com/nfraxlab·alikhatami.dev

Technical Product Leader with Staff-level engineering depth. Six years building developer platforms, AI/LLM automation systems, and API governance tools at enterprise scale. Rebuilt Chase's entire API onboarding lifecycle—cutting governance from 2 months → 1 week and documentation from 4–5 weeks → minutes using LLM pipelines, RAG, graph-based scoring, and OpenAPI-first architecture. Founder of nfrax, a 100+ star open-source SDK ecosystem powering backend, AI, and fintech workflows.

Governance approvals: ~2 months → ~1 week · Documentation: ~4 weeks → minutes · ~90% fewer governance/compliance errors

Product & Strategy:Roadmap Planning, Stakeholder Management, OKRs & Metrics, Agile/Scrum, User Research
Agentic Systems:LLMs, LangGraph, RAG, MCP, NLP
Distributed Backend:Java, Spring Boot, Python, Kafka, FastAPI
Cloud & Delivery:AWS, Terraform, Spinnaker, Splunk
Developer Experience:SDK Architecture, TypeScript, Documentation Systems, Type-Safe Interfaces
Data & Reliability:SQL, NoSQL, Vector Search, PySpark

Professional Experience

VP / Lead Software Engineer + Technical Product Lead

·JPMorgan Chase & Co.—New York, NY
Mar 2024 – Present
Promoted into hybrid Staff-level engineering + product leadership role to execute the modernization and automation strategy I defined for Chase's 4,000+ API ecosystem.
  • Designed the full automation architecture for API governance, documentation, and readiness scoring using LLMs, RAG, and graph-based state machines.
  • Compressed governance from 2 months → 1 week via deterministic scoring, evidence capture, and automated remediation tied directly to OpenAPI updates.
  • Built parallelized LLM documentation generation with hallucination mitigation, ML-based validation, and spec-driven consistency checks—cutting cycles from 4–5 weeks → minutes.
  • Architected graph-driven progression models for governance states, readiness scoring, compliance gates, and remediation workflows.
  • Built MCP-powered agentic systems answering ownership, readiness, and standards queries across thousands of APIs.
  • Drove adoption across the firm; platform is now the CCB standard for onboarding and readiness.
  • Collaborated with partner integration teams building Disney eGift APIs, Amazon Card APIs, and loyalty systems using Java, Spring Boot, AWS, Terraform, and resilient event-driven designs.
  • Recognized in executive briefings and CCB townhalls; work presented to CTO Gill Haus.

Technical Product Manager — API Platform

·JPMorgan Chase & Co.—New York, NY
Jan 2023 – Mar 2024
Product owner for API governance and documentation modernization across Chase CCB. Promoted to VP.
  • Mapped organizational friction across onboarding, governance, documentation, and partner readiness.
  • Defined multi-phase modernization roadmap moving documentation from inconsistent Word docs → standardized Markdown → spec-driven autogeneration.
  • Shifted OpenAPI specs to source-of-truth, improving governance accuracy and partner trust.
  • Authored PRDs and NFRs covering auditability, SLOs, risk controls, and fail-safe behaviors.
  • Designed API-driven documentation storage and retrieval, replacing file-passing with structured, scalable systems.
  • Result: Platform became enterprise standard for API onboarding and partner delivery.

Senior Associate Engineer — ML & Platform

·JPMorgan Chase & Co.—New York, NY
Sep 2021 – Dec 2022
Built ML-driven risk forecasting pipelines and full-stack cloud cost visibility platform adopted org-wide.
  • Built ML-driven risk forecasting pipelines; migrated Pandas workloads → PySpark for scalability.
  • Developed full-stack platform (Python/Django + React) for cloud cost visibility and resource planning, adopted org-wide.
  • Created reusable CI/CD patterns used across CIB engineering teams.

Founder & Lead Developer

·nfrax (Open Source · 100+ Stars)—Remote
Jul 2024 – Present
Open-source SDK ecosystem powering backend frameworks, AI agent workflows, and fintech integrations.
  • Built 4 MIT-licensed SDKs: svc-infra (backend framework), ai-infra (LLM/RAG workflows), fin-infra (fintech integrations: Plaid, Teller), robo-infra (robotics/IoT toolkit).
  • Designed type-safe interfaces, retries, caching, service abstraction layers, and resilience patterns.
  • Unified APIs that reduce boilerplate and speed up delivery; adopted by open-source developers and early startups.

Founder & Lead Engineer

·QuantTech Markets—New York, NY
Sep 2019 – Feb 2021
Founder & lead engineer of an ML/NLP-driven equities research and trading platform that outperformed S&P 500 by 5–7%.
  • Built algorithmic trading engine using Python, ML, and NLP models—outperformed the S&P 500 by 5–7%.
  • Sold the backend to a trading firm while retaining usage rights.
  • Built full-stack platform (React + Python) with reproducible backtesting, portfolio analytics, and automated deployments.

Key Projects

AutoChannel

API governance + documentation automation — ~80% faster governance reviews and consistent OpenAPI readiness across 4,000+ APIs.

LangGraph, MCP, LLMs, Vector Search, OpenAPI

nfrax

SDKs that remove backend boilerplate — 3 MIT-licensed SDKs that cut boilerplate and speed delivery.

Python, FastAPI, MCP, Vector Search, Plaid

MCP Servers

Standardized tool invocation for agents — Repeatable, secure agent workflows adopted org-wide.

MCP, TypeScript, Python, VS Code API

Education

Master of Science in Data Science — Bellevue University (2023), GPA 4.0 • Summa Cum Laude
Bachelor of Science in Quantitative Finance — Hofstra University (2021), GPA 3.2

Certifications

Agile Project Management— Google
2021
Agile with Atlassian Jira— Atlassian
2021
AWS Cloud Practitioner— Amazon Web Services
2025
Algorithms & Data Structures— MIT
2023
Intermediate Machine Learning— Kaggle
2023

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Last updated: January 2026