Forward Deployed Product Manager

Bolo AI•Houston, TX

3d•Hybrid

About The Position

Bolo AI is building the AI company for heavy industry, focusing on sectors like energy, utilities, manufacturing, and industrial operations. These sectors have been underserved by modern software and AI, and Bolo AI aims to change this with AI solutions tailored for their operational realities. Customers are already leveraging Bolo AI to predict equipment failures, identify cost impacts, automate workflows, and utilize industrial data. Bolo AI is a small, AI-native team backed by prominent venture capital firms, dedicated to improving the speed, safety, and efficiency of industrial work. The Forward Deployed Product Manager will be responsible for customer engagement outcomes, from initial problem discovery to delivering tangible impact. This role bridges customer interaction, go-to-market strategies, and engineering efforts. The individual will delve into complex operational workflows, define Minimum Viable Products (MVPs), translate customer needs into product requirements, and drive engagements to achieve measurable business value. The core competency for this role is transforming ambiguity into concrete results. The position requires working with customers who have intricate workflows, fragmented data, strict security requirements, and high expectations. The primary objective is to bring clarity, sequence work effectively, manage trade-offs, and ensure that developed solutions are both useful for the customer and reusable for Bolo AI. The success metric for this role goes beyond simply delivering promised features; it's about creating so much value that customers become reliant on Bolo AI. The Forward Deployed Product Manager will be accountable for customer success and product learning, identifying repeatable patterns to inform product direction and scalable delivery processes. This role is customer-facing and requires regular team collaboration, customer meetings, on-site discovery, and travel, which may reach up to 50% during intensive periods.

Requirements

6–8+ years of experience in a high-ownership, customer-facing role such as consulting, forward-deployed product, enterprise software implementation, solutions, technical delivery, product management, or business operations.
A track record of running complex client-facing work under ambiguity, including scoping problems, aligning stakeholders, managing tradeoffs, and driving to a concrete outcome.
Strong commercial judgment. You understand that customer success, expansion, renewal, and product direction are connected.
Strong technical fluency. You should be comfortable reasoning through data, integrations, AI workflows, implementation constraints, and tradeoffs with engineers.
Clear product judgment. Direct PM experience is not required, but you should be able to define MVP scope, write clear requirements, make prioritization tradeoffs, and distinguish customer-specific requests from reusable product patterns.
Excellent communication with executives, operators, engineers, and data teams. You can push back without becoming defensive or overly accommodating.
Evidence that you can operate in a very early-stage startup environment: low structure, high ambiguity, fast context switching, and no perfect playbook.
Real curiosity about AI. You actively experiment with AI tools and can think critically about where they work, where they fail, and what it takes to make them reliable in production.

Nice To Haves

Exposure to energy, oil and gas, heavy industry, applied AI/ML, or LLM-based products is a strong plus.

Responsibilities

Own customer engagements from discovery through deployment, adoption, and measurable impact.
Build credibility with customer stakeholders across field teams, technical teams, executives, and commercial buyers.
Immerse yourself in the customer’s world through both their data and their day-to-day workflows.
Translate messy customer problems into clear problem statements, MVP scope, data requirements, user stories, and product requirements.
Partner with engineering to turn customer workflows and datasets into stable, extensible AI-powered solutions.
Manage tradeoffs across customer urgency, technical complexity, commercial value, and long-term product reuse.
Scope phased deployments that create value quickly without creating unsustainable custom work.
Lead customer rollout and adoption so shipped solutions become part of real workflows.
Stay close to expansion, renewal, and commercial outcomes, not just delivery milestones.
Identify repeatable patterns across engagements and turn them into product and delivery processes as Bolo scales.