Product Manager

BackOps-AISan Francisco, CA
Onsite

About The Position

We build AI-powered software for complex supply chain and logistics workflows used by large enterprises. Our users work in operational environments where decisions have real business consequences, workflows often span multiple systems and stakeholders, and the right product solution is rarely obvious from a feature request alone. We're ~50 people, headquartered in San Francisco, and backed by investors who support category-defining companies early and with conviction: our Series A was led by Theory Ventures, with participation from Gradient, Construct Capital, and 10VC. The problem is real, the timing is right, and we're building the team that introduces AI where it matters. You will work closely with customers, engineering, design, go-to-market teams, and company leadership to identify important problems, determine where AI can or cannot meaningfully improve workflows, translate product strategy into shippable solutions, and continuously improve those solutions based on evidence. You’ll report to the Head of Product. Because we are an early-stage company, we are looking for someone who understands that the right product process depends on the stage of the company and the importance of the problem. You should be equally comfortable defining product strategy, conducting customer research, analyzing data, writing a detailed product specification, creating a lightweight prototype, or helping close the gaps needed to get a straightforward feature shipped.

Requirements

  • Approximately 4+ years of product management experience.
  • Experience building B2B software products.
  • Strong experience designing products for non-developer business users, particularly users performing complex business or operational workflows.
  • Excellent written and verbal communication, including the ability to explain priorities, tradeoffs, product decisions, and strategy clearly to different audiences.
  • Comfort working with data and using quantitative analysis alongside qualitative research.
  • Curiosity about AI and the ability to independently learn about rapidly evolving AI technologies and translate technical developments into potential product opportunities.

Nice To Haves

  • Experience building products for large enterprises, understanding of enterprise buyers and their requirements.
  • Experience navigating complex, multi-stakeholder enterprise purchasing and implementation processes.
  • Experience with supply chain or logistics enterprise software.
  • Experience with AI-powered products, agents, LLM applications.

Responsibilities

  • Help define and communicate the product vision, strategy, and roadmap based on company goals, customer needs, market opportunities, and technical possibilities.
  • Build clear product rationale and communicate not just what we are prioritizing, but why.
  • Anticipate that priorities will change as we learn and help the team make progress without over-engineering plans around assumptions that may quickly become obsolete.
  • Bring stage-appropriate product judgment: know when directional evidence is enough, when to build something lightweight, and when an investment needs to be built for scale.
  • Determine where AI can genuinely improve the work performed by customers rather than simply adding AI functionality to existing workflows.
  • Explore how AI systems should interact with users across areas such as automation, recommendations, decision support, exceptions, approvals, explanations, and human oversight.
  • Independently research emerging AI technologies, models, techniques, and product patterns and determine which developments are relevant to our product.
  • Work closely with engineering to prototype potential AI-powered solutions.
  • Translate product strategy and customer problems into clear, shippable product components, partnering closely with engineering from problem definition through implementation.
  • Break ambiguous initiatives into incremental releases that generate customer value and learning, while identifying edge cases, risks, and key decisions early.
  • When appropriate, independently complete straightforward product, design, analytical, prototyping, or technical work needed to move initiatives forward.

Benefits

  • early 0 → 1 product formation, launches, and iteration
  • heavily involved with different stakeholder team’s processes as we discover the new way of working in this AI-native age
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