/ Résumé

Maxwell Holmes

Washington, DC · [email protected] · 240.273.2323

Founder and AI-native product leader, 10+ years building customer-facing products 0-to-1, with the last 3 years developing LLM/ML-powered workforce, hiring, and talent intelligence platforms. Turns ambiguous user needs across executives, managers, operators, recruiters, and frontline employees into product strategy, requirements, prototypes, and shipped enterprise solutions with measurable business and human outcomes. Founded and exited a venture-backed startup, led an 11-person cross-functional team, and currently leading product and technology development for a hiring and talent intelligence platform.

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/ Experience

PerfectHire — AI-powered hiring platform for hourly and enterprise workforces · Remote

Chief Product Officer → Chief Technology Officer

Sept 2025 – Present
  • Set product and platform strategy for a talent intelligence layer across 10 enterprise customers; translated recruiting manager, HR, executive, and hiring-team needs into user journeys, business requirements, prototype priorities, success metrics, and adoption plans; named the 2026 Most Innovative or Emerging Talent Acquisition Tech Solution by Lighthouse Research.
  • Architected a "digital twin" product framework that moved matching beyond keyword search to infer adjacent skills, transferable experiences, and job-fit signals via embeddings-based partial credit across skill families and semantic analysis; secured engineering, sales, and executive alignment and buy-in as a core product differentiator.
  • Designed a recruiter productivity and explainability framework with composite real-time scores for workload, focus, and balance; replaced fragmented, backward-facing metrics with forward-looking decision support that helps individual recruiters prioritize work and managers identify team capacity imbalances. In a 20-user comparison test against legacy-style dashboards, twice as many recruiters said the new framework would shape their daily prioritization as reported being influenced by their existing dashboards (16 vs. 8 of 20).
  • Built and shipped an hourly-workforce hiring and management pilot product solo using AI-orchestrated development (Claude Code); rapidly translated discovery insights and business requirements into core specifications; pilot deployments across 5 enterprise customers delivered 46% reduction in time-to-hire for understaffed shifts, 33% reduction in over-hiring, and 8% labor-share improvement.
  • Translated 30 discovery interviews with recruiting managers and hiring teams into reimagined core workflows and requirements; collapsed multi-week feedback cycles into single-conversation alignment; managed porting the inherited codebase from .NET/Blazor to React to enable faster development velocity with limited engineering resources.
  • Owned ML/AI architecture and experimentation; defined customer-success metrics, experiment design, production-readiness standards, and tradeoffs across live vs. batch inference, microservice composition, and build-vs-integrate decisions. Deployed solutions and experiments to design partners, with 6 of 10 incorporated into core product releases.
Conduit — venture-backed AI scheduling & labor-matching platform for QSR/retail · Pittsburgh, PA

Founder & CEO

Named one of the most disruptive MBA-led startups of 2023

May 2023 – Sept 2025
  • Founded and scaled an AI-driven shift-scheduling and labor-matching product for hourly workforces; raised a $500K pre-seed, hired and managed a team of 11 across engineering, design, and ops; exited via acquisition by a strategic partner.
  • Shipped v1 to multi-location pilot deployments; defined success criteria across multiple user personas and workflows; validated against baselines, achieving 95% reduction in time-to-schedule, 35% reduction in turnover, 96 NPS, and $500K in annualized customer savings.
  • Led a customer-driven pivot to a cross-business labor-sharing model; expanded the available labor pool for operators while increasing weekly income for workers — becoming the key product differentiator and strengthening the core business case.
  • Ran 150+ customer discovery interviews across franchise operators, store managers, and frontline workers; translated insights into engineering specs, sales positioning, and pricing models across multiple GTM iterations; ran weekly product, engineering, and GTM alignment meetings and daily standups.
Cognex Corporation — leading developer of machine-learning and computer-vision hardware · Natick, MA

Product Marketing Manager, Intern

Jun – Aug 2022
  • Diagnosed a structural margin failure within a product line running at roughly half its target margin after a new edge-computing camera replaced a high-volume, low-cost model; proposed and won pilot approval for per-image subscription pricing, converting a capex sale into recurring revenue with up to 10x projected lifetime revenue per device.
  • Identified a new SMB drug-manufacturer segment reachable via system integrators; modeled $10M five-year revenue uplift; GTM pilot approved before departure.
Meso Scale Diagnostics — manufacturer of research equipment for the life sciences · Rockville, MD

Mechanical Engineer II (de facto Product Manager)

Sept 2019 – Jul 2021
  • Owned customer discovery, requirements, and roadmap across hardware, firmware, and software on a two-year R&D platform; reframed the position from "precision pipetting" to "maximize researcher walk-away time" via end-user discovery, securing cross-discipline leadership buy-in (EE/ME/SW).
  • Built an automated test framework (Python, APIs, custom firmware) that cut cycle time 70% and improved platform performance 50%; delivered two prototype phases ahead of schedule while outperforming the market leader by 40%.
Bio-Imaging and Machine Vision Lab — public/private group developing novel robotics · College Park, MD

Mechanical Engineer → Lead Mechanical Engineer → Lead Program Manager

May 2015 – Sept 2019
  • Led 0-to-1 product development across multiple industrial computer-vision machines deployed with commercial customers (oyster processors, strawberry growers, athletic apparel, pharma OEMs); inventor on 3 patents.
  • Designed an automated strawberry-processing system with 16 tons/hour throughput; saved 15% additional fruit yield and thousands of weekly labor hours per facility.
  • Identified $6M in research and commercial grant funding across NSF, USDA, and state agencies; structured proposals balancing research credibility and commercial deployment viability.
  • Co-founded a spinoff to commercialize the lab's oyster-processing platform; modularized the architecture (40% BOM-cost reduction), deployed 5 commercial units, and negotiated a six-figure acquisition when capital and TAM constraints made venture-scale continuation strategically irrational.

/ Education

Carnegie Mellon University, Tepper School of Business — Pittsburgh, PA

Master of Business Administration (MBA)

2023

Entrepreneurship Track; concentrations in Technology Strategy, Organizational Behavior, and Marketing. Vice President, Graduate Business Association; Business Development Lead, CMU Autonomous Racing. Honors: David Tepper Merit Scholarship, Spirit of Service Scholarship, WL Mellon Legacy Fellowship.

University of Maryland, College Park — College Park, MD

B.S., Mechanical Engineering

2015

Honors: Cum Laude, Dean's Academic Scholarship.

/ Technical Skills

AI-native dev
Claude Code, Codex, Cursor, Replit, Hermes Agent Framework — shipped customer-facing product end-to-end via LLM-orchestrated coding and architectural direction.
Stack
React, TypeScript, Supabase, vector databases, semantic embeddings, LLM APIs, RESTful microservices (architected and deployed).
Applied ML
Problem definition, data-collection design, and model evaluation; defined ML opportunities, evaluated build-vs-integrate tradeoffs, and shipped ML-enabled features into production.
Tools
Python, SQL, Figma, Jira, Linear, Notion, Cloudflare Workers & Pages.