Hire an AI product manager who scopes what's real.
Someone who scopes AI features realistically and ships the roadmap, not just the vision.
AI product management has different failure modes than regular product management: scope creep from what a model 'might' do, success metrics nobody defined before launch, roadmaps built on demos instead of evals. Our AI product managers bring the discipline of scoping features against real model capability and shipping against measurable outcomes.
- Seniority
- 5+ years product management, 2+ years specifically on AI/ML features
- Background
- AI feature scoping, success-metric definition, cross-functional work with engineering and design on AI products
What they'll actually do.
Not a job description — the work this person owns from their first sprint, inside your codebase and your process.
Work this bench has shipped.
Gigbase — Multi-Tenant Agency Operating System
A multi-user agency management portal: projects, teams, clients, contracts, invoicing, real-time chat, meeting scheduling, and an admin-trained AI knowledge assistant — one subscription-based workspace.
Inflectiv Helios — Multi-Assistant AI Platform
A multi-user AI assistant platform: specialized assistants per knowledge domain, conversational UI with history and personalization, Google Calendar/Meet integration, and full prompt observability — built to absorb new AI capabilities.
Beyond AIO — AI Business Management & Analytics Platform
An all-in-one AI-powered business platform: predictive analytics, competitor analysis, CRM, HRM, financial management, task management, and cross-channel marketing with real-time campaign optimization.
Disclosure — founder-owned venture
Tell us the role, the stack, and when you need them started.
Every figure has a name behind it.
No rounded-up vanity metrics — each number below is tied to a specific, named engagement this bench shipped.
From intro call to embedded.
Matched by people who've scoped AI features against real model limits, not a roadmap built on a demo.
Intro call
Confirm the role, stack, and team fit in one call.
Match
We propose 1–2 people from the bench who fit the work, not a generic pool.
Trial week
A real first week of work before any longer commitment.
Embed
Full participation in your standups, sprints, and tooling.
If the fit isn't right, we replace them inside two weeks — no argument, no fee for the swap. You'd rather we caught it early, and so would we.
Asked on every first call.
Not typically. An AI product manager sits between engineering and the business — scoping features against real model capability, defining success metrics before build starts, and prioritizing across AI and non-AI work — rather than implementing. The bar is being able to read an evaluation report and argue with it, not to write the pipeline that produced it.
Yes, and that is the default. A staff-augmentation AI product manager works inside your backlog, your rituals and your standups, not in a separate vendor environment.
An AI product manager typically starts within one to two weeks of the intro call. We match from an existing bench rather than opening a cold hiring pipeline, so the limiting factor is usually your onboarding and access paperwork rather than our recruiting.
Every AI product manager placement carries a two-week replacement guarantee, with no argument and no fee for the swap. We would rather replace someone in week two than have you carry a bad fit for a quarter.
No. An AI product manager is engaged day-rate or monthly, month-to-month after a four-week minimum. No tiers, no bundled products, no notice period designed to trap you.
You do. Roadmaps, specifications, success metrics and evaluation criteria an AI product manager produces belong to your company and stay yours whether or not the engagement continues. They live in your tools from the start, so there is nothing to hand back at the end.
One call. Then a name, not a pipeline.
- 30 minutes with a senior engineer, not a recruiter
- Free and no-obligation — bring the role and the stack
- You leave knowing who we'd match and how fast they can start
- We reply within one business day
Anthropic-certified engineering capacity for Claude-native products and agents.
Senior LLM application engineering, without the vendor lock-in.
Agent and workflow-automation engineering, embedded in your team.
Full-stack web and mobile engineering, AI-accelerated, senior-owned.
Fractional technical leadership for teams that need direction, not headcount.
Fractional AI leadership — roadmap, governance, and vendor decisions.
Retrieval pipeline engineering — the discipline behind every trustworthy RAG system.
Deployment, monitoring, and cost control for production AI systems.
Pipelines, warehousing, and AI-ready data infrastructure.
Systematic prompt and context design, tested against real outcomes.
Let's put AI to work in your business.
A 30-minute call. You bring the workflow or the roadmap — we'll tell you what's feasible, what it costs, and what we'd build first.