Job description

About Us: Bolo AI is building the AI company for heavy industry. These are the sectors the world depends on: energy, utilities, manufacturing, and industrial operations. They have been underserved by modern software and AI for too long. We are changing that with AI built for their messy, high-stakes operational reality. Customers are already using Bolo to catch critical equipment failures, recover hidden cost impact, automate operational workflows, and put decades of industrial data to work. Backed by True Ventures, Benchstrength, Accomplice, Analog Ventures, and Beat Ventures, we are a small, AI-native team working close to the customer to make their daily work faster, safer, and better. Role Overview: We’re hiring a Forward Deployed Product Manager to own customer engagement outcomes from problem discovery through shipped impact. This is not a traditional roadmap PM role, and it is not an implementation-only delivery role. You will sit at the intersection of customer, GTM, and engineering: understanding messy operational workflows, scoping the right MVP, translating customer needs into product requirements, and driving the engagement to measurable business value. The core skill is turning ambiguity into shipped outcomes. You will work with customers who have complex workflows, fragmented data, security constraints, and high expectations. Your job is to create clarity, sequence the work, manage tradeoffs, and make sure what we build is useful for the customer and reusable for Bolo. For every customer engagement, especially pilots, the bar is not “did we deliver what we promised?” The bar is: did we create so much value that the customer does not want to live without Bolo when the pilot ends? This role is accountable for helping us reach that level of customer pull. You will be accountable for both customer success and product learning. That means you are not just delivering one-off customer requests. You are expected to identify repeatable patterns, shape product direction, and help us build scalable delivery processes as we grow. Note: This role can be based in Palo Alto, CA or Houston, TX . In either location, this is an in-person, customer-facing role. You should expect regular team collaboration, customer meetings, on-site discovery, and travel. Travel will vary by customer phase and may reach up to 50% during intensive discovery, deployment, or expansion periods. What You’ll Own: 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. What Success Looks Like: You help pilots become must-have deployments by creating clear, measurable customer value. You build trust with customers, engineering, GTM, and founding team by creating clarity and driving outcomes. You turn customer-specific learning into reusable product and delivery patterns. Who We’re Looking For: 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. Exposure to energy, oil and gas, heavy industry, applied AI/ML, or LLM-based products is a strong plus. What We Offer: Bolo AI is a technology startup headquartered in Palo Alto, backed by True Ventures, Benchstrength, Accomplice, J Ventures, and Beat Ventures. We offer competitive compensation, generous PTO, flexible working hours, an office in Palo Alto for in-person collaboration, and the following: Competitive Compensation: A strong base salary Ownership & Impact: Equity options so you can share in our success as we grow and shape the future together. Hybrid Work Environment: Enjoy a flexible hybrid schedule—collaborate in person and work from home. Growth & Opportunity: Join us at a pivotal stage where your contributions will have a direct impact on our journey. As we grow, so will your opportunities.

Requirements

Must-haves

We’re hiring a Forward Deployed Product Manager to own customer engagement outcomes from problem discovery through shipped impact.
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.
You help pilots become must-have deployments by creating clear, measurable customer value.
You build trust with customers, engineering, GTM, and founding team by creating clarity and driving outcomes.
You turn customer-specific learning into reusable product and delivery patterns.
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.
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.
Exposure to energy, oil and gas, heavy industry, applied AI/ML, or LLM-based products is a strong plus.

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aimlllm

Platform: greenhouse
Effort: quick

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