AI Product Manager

AHEAD

28d•$200,000 - $250,000

About The Position

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation. At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD. We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived. We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD. AHEAD is scaling its unified AI portfolio to deliver measurable business outcomes for clients through repeatable frameworks, accelerators, and productized solutions. The AI Product Manager will be pivotal in operationalizing our âbuild-to-scaleâ approachâconnecting strategy, engineering, and client value across the full enterprise AI outcomes: Strategy, People Enablement, Applications, Platforms, Operations, and Security. This role will drive both internal enablement and client-facing delivery, with hands-on demos leveraging AWS, NVIDIA, and other leading stacks. Youâll work closely with the AI Hiveâa cross-functional team at AHEAD that brings together strategy, solution development, enablement, and delivery experts to accelerate enterprise AI adoption and ensure every solution is aligned to client outcomes and best practices. Role Scope & Focus Internal-facing (first 6 months): Develop and enable prioritized AI solutions across platform, agentic, application, and security domains for internal adoption. Build demos and prototypes to validate solution approaches and accelerate time-to-value. Package solutions for scale (documentation, reference architectures, enablement kits). Client-facing (6â12 months): Deliver client engagements with measurable impact and repeatable patterns. Lead solution intake, prioritization, and stakeholder alignment across AHEADâs AI Hive, GTM, and delivery teams. Facilitate decisions balancing strategic value, technical feasibility, and operational readiness.

Requirements

6â10+ years in Solution/Product Management (platforms, applications, internal tools, or enterprise solutions).
Track record of shipping high-impact solutions in agile environments.
Experience delivering GenAI/AI use cases (prompt-driven workflows, RAG, agentic orchestration, analytics assistants).
Strong product discovery and solution design skills (journey mapping, experimentation, data-informed decisions).
Excellent stakeholder engagement across engineering, design/UX, security, and GTM.
Fluency in backlog management, release planning, and telemetry-driven iteration.

Nice To Haves

Familiarity with modern AI stacks (LLMs/APIs, vector databases, orchestration frameworks).
Experience packaging frameworks/accelerators for sales teams.
Hands-on experience with AWS, NVIDIA, and other Data, AI and Cloud technologies.

Responsibilities

Own and evolve the roadmap for enterprise AI solutions (platforms, agentic AI, applications, security, operations).
Translate business objectives and demand signals into product bets, milestones, and outcomes.
Define problem statements, value hypotheses, and success metrics.
Run intake/triage with AI Hive, GTM, and delivery leaders.
Align priorities, sequencing, and release scope.
Facilitate decisions balancing strategic value, technical feasibility, and operational readiness.
Convert strategy into executable work (epics, stories, acceptance criteria, release plans).
Lead agile ceremonies and feedback loops with engineering, design, and solution owners.
Drive discovery and validation (user interviews, prototypes, dogfooding).
Develop demos/POCs using AWS/NVIDIA and other enterprise AI hyperscalers.
Package solutions for scale (documentation, reference architectures, enablement kits).
Build repeatable accelerators and sales engineering content for internal and field use.
Maintain playbooks for scalable, repeatable Product Ownership.
Define, track, and communicate KPIs (adoption, cycle time, quality, ROI).
Publish roadmap updates and value stories for executive stakeholders.