Muneeb Ahmed

AI product manager who builds hands-on and thinks in evaluation — and who owns an AI product end to end, from customer discovery to prompt design to production quality. Founder of an AI platform where the hard problem is exactly the one that matters in production: making model output defensible through eval frameworks, a clear quality bar, and grounding in real success criteria. I bring a venture-builder's full-stack ownership to product management — I don't just define what to build, I've validated it with customers, written and iterated the prompts, set the evaluation methodology, and owned the performance.

Strongest where AI products meet high-stakes decisions and need judgment about what to build, how to measure it, and how to keep it trustworthy.

Founder & Product Lead at Octolynx (2025-01 – Present)

AI predictive talent-assessment platform tackling mis-hires that cost up to $240K per candidate — from fully auditable, trackable job descriptions to a three-dimensional weighted-scoring assessment · Pre-launch, Beta 2026

• Owned an AI product end to end: defined the problem, the metrics, and the roadmap for an AI platform scoring high-stakes decisions in an $18B market — the same full-lifecycle ownership this role calls for, from discovery to live product.
• Prompt design, evaluation & quality bar: designed the operational evaluation frameworks, auditability engine, and quality thresholds that make model output defensible and reproducible — writing and iterating the logic behind the AI, then measuring performance against explicit criteria.
• Semantic text analysis (two patents): secured two filed provisional patents in semantic text analysis for high-stakes assessment — extracting structured, defensible signal from unstructured text, the core technical problem in contract and procurement intelligence.
• Discovery with customers: ran 12+ structured discovery interviews with decision-makers across biotech, pharma, GTM-intelligence, and operations to size the opportunity and pressure-test the product; selected to the Harvard Business School Foundry (top-10% cohort).
• Built it hands-on: architected the full technical system end to end and directed a small technical team through the move from prototype to production-grade infrastructure; own UI/UX end to end in Figma.

Team Lead at CarJudo (2026-01 – 2026-12)

AI decision-intelligence engine de-risking used-car purchases · led a team of 5 (GTM, sales, GM, software) to VC pitch

• Led an AI product from concept to investor pitch: directed a 5-person team through the full lifecycle — problem definition, AI product envisioning, prototyping, business model, and a VC-level pitch deck — for CarJudo, an AI decision-intelligence engine de-risking the $1T US used-car market.
• Turned unstructured data into a decision signal: designed the product to surface $3,000–$5,000 in unpriced annual maintenance exposure and compress fragmented research into a 60-second 1–100 confidence score — the same extract-signal-from-messy-data pattern that underpins contract and procurement intelligence.
• Coordinated across functions: aligned teammates from GTM, sales, general management, and software development around a single product and go-to-market narrative — the cross-functional leadership an AI PM role runs on.

SynthResume — Deterministic RAG synthesis at Independent (2025-01 – 2026-12)

Tool that turns a portfolio into a tailored, ATS-ready resume via RAG · solo end-to-end AI build

• Solved the consistency problem: built a full RAG pipeline with deterministic post-processing guardrails so outputs are reproducible and grounded in real source content (same inputs → same output) — directly addressing hallucination and quality-bar consistency for high-stakes AI features.

Credit-Risk Predictive Model at Independent (2025-01 – 2025-12)

ML model predicting borrower financial distress · capstone project, Machine Learning coursework (MBA, Babson)

• Framed metrics as product decisions: built an ML model on 150K observations, treating the precision/recall trade-off (catching defaults vs. false alarms) as a product decision, not just a metric — and handled severe class imbalance to preserve data integrity.

Operations & New-Vertical Consultant at Independent Practice (2021-01 – 2024-12)

New-vertical launches & turnarounds across 4 clients

• New service line (JJ HealthCare, a Canadian medical-equipment provider): took a recurring-revenue equipment-rental line from idea to launch — market research, pricing, and demand generation — for a 3x sales increase while cutting acquisition cost 30%.
• GIS vertical (DP World, global ports & logistics operator): personally managed every key stakeholder on an inaugural geospatial-mapping project, replacing scattered email threads with a lean Smartsheet ticketing workflow — enabling rapid iteration, saving significant hours, and delivering ahead of schedule; commercial negotiation I led helped the client secure strong project margins.
• Process automation (Dupont Academy, a private tutoring institute): collapsed a 27-step manual student-intake process into one automated sequence — 92% time savings, 10x capacity with no added headcount, 99% fewer errors.
• Revenue turnaround (Galaxy Geomatics, a drone-survey & geospatial firm): rebuilt a pandemic-stalled operation's pipeline and collections — 200% revenue growth and a 60% reduction in receivables.

Founder & Managing Director at ILMATS (2017-01 – 2020-12)

Systems-integration firm I founded (CCTV, access-control & IT infrastructure)

• Built and scaled a business from zero: bootstrapped the firm and delivered 200+ high-stakes CCTV, access-control, and IT-infrastructure projects for institutional and corporate clients — owning strategy, operations, and the P&L end to end.
• Engineered a repeatable growth engine: designed a lead-maturity system that lifted conversion from 50% to 90%, turning ad-hoc demand into a predictable sales operation.

Business Development Lead at Petrocon (2015-01 – 2017-12)

Led overseas market entry for an industrial-services firm

• Launched a market from zero: stood up the firm's overseas branch end to end — office, compliance, and sales lifecycle — building a 100+ qualified-lead funnel and two cross-border JV MOUs that seeded growth to multimillion-dollar revenue and 2,000+ headcount.

Applied Consulting & Field Projects at Various Clients (2024-01 – 2025-12)

Graduate applied and field-consulting engagements — real clients and problems, delivered in teams. Included to evidence breadth of applied product and strategy work.

• Product commercialization strategy (Mass General Brigham Innovation): led a go-to-market study for an objective pain-assessment (fNIRS) medical device — mapped 33 competitors, ran 12+ clinician and manufacturer interviews, and sized the opportunity (TAM $53B / SAM $21.5B). Recommended pivoting from the operating room to higher-fit adjacent markets and delivered a phased 510(k) regulatory-and-funding roadmap ($3–5M, 24–30 months).
• Market adoption modeling (Raytheon Technologies, aerospace & defense): field consulting project (team of 5) — built adoption and market-sizing models to inform go-to-market strategy for a public-safety technology initiative.
• GTM strategy & product innovation (SmartBill, a billing-software company): advised on go-to-market strategy and product-innovation direction — customer and market analysis translated into actionable positioning and roadmap input.
• M&A valuation modeling (Mechanix Wear, a work-glove maker / Fortive): modeled a $264.55M acquisition at 10.5x EBITDA, projecting 20%+ IRR and 1.28x DSCR across bull / base / bear scenarios — the analytical rigor behind sound product and investment decisions.

STEM MBA in Entrepreneurship, Machine Learning & Business Analytics – Babson College (2024-01 – 2026-12)

B.Eng. in Mechanical Engineering – Vasavi College of Engineering (2008-01 – 2012-12)