Mohamed Mohamed Mohamed Feroze Ajmal

About Mohamed Mohamed Mohamed Feroze Ajmal

I shipped an LLM-powered product at a regulated HR-tech company — with safety controls, audit logging, and fallback patterns — before most teams finished their AI strategy decks.That\'s the kind of Product Manager I am.I build AI-powered experiences and API integration products at Verified First, where background screening meets HR-tech automation. My work sits at the intersection of large language models, REST APIs, and ATS/HRIS partner ecosystems — and I own it end-to-end: discovery, requirements, delivery coordination, QA readiness, and rollout.A few things I\'ve shipped:→ Led a 0→1 LLM-powered status experience for regulated workflows — built guardrails, constrained retrieval, audit logging, and fallback patterns to keep outputs reliable and safe.→ Rebuilt our partner integration onboarding process from scratch — standardized playbooks, stage gates, and templates cut launch timelines from months to ~3 weeks.→ Built repeatable integration patterns for ATS/HRIS partners — reducing implementation variance and edge-case failures across the board.I think in systems. I care about whether something actually works in production — not just in a demo. And I\'ve learned to build AI products the right way: with safety controls, evaluation criteria, and operational QA baked in from day one.Stack I work in: Workato · REST APIs/Webhooks · Vertex AI · SQL · Python · Jira/Confluence · LLMs/RAGMS in Management of Technology from ASU (GPA: 4.17).If you\'re building AI products in HR-tech, fintech, or any regulated space — or if you\'re looking for a PM who can navigate LLMs without waving a magic wand — let\'s connect. Open to conversations about PM roles, AI product collaboration, or just nerding out on how to build reliable AI products.

Experience

1. Product Manager

   Verified First

   Jan 2025 — Present

   Reduced integration partner launch timelines by ~70% — from 3+ months to ~3 weeks — by introducing standardized onboarding playbooks, stage gates, and reusable templates that improved predictability across ATS/HRIS rollouts- Led 0→1 delivery of an LLM-powered status experience for regulated HR workflows — from discovery through QA sign-off — incorporating guardrails, constrained retrieval, audit logging, and fallback patterns to ensure safe, consistent outputs- Defined release metrics and QA acceptance criteria across AI and integration releases, reducing ambiguity in rollout readiness decisions and enabling faster cross-team sign-off.

Education

• Great Lakes Institute of Management

  PGP, Data Science and Engineering

• Anna University

  Bachelor of Engineering - BE, STEM

• Arizona State University

  Master of Science - MS, Management of technology, Product Management

  2023 — 2024