Product Manager, AI Agents

The posting, as Backops Ai wrote it

About BackOps

BackOps is building the AI resolution layer for companies that make or move physical goods.

The physical economy still runs on a fragmented web of ERPs, WMSs, TMSs, carrier and vendor portals, email, spreadsheets, legacy systems, and the people who know how to hold all of it together. When something breaks, whether a shipment is delayed, an order changes, a claim needs to be filed, a document is missing, someone has to gather context across systems, determine what should happen next, take action, and make sure the problem is actually resolved.

BackOps automates that work.

Our platform, Relay, deploys AI operators that understand operational workflows, work across the systems our customers already use, take action, navigate exceptions, and carry work through to resolution. We aren't building another dashboard or copilot. We're building the execution layer that sits between systems and gets the work done.

We recently raised a $42M Series B led by Insight Partners, just six months after our Series A, and are scaling across some of the largest companies in logistics, manufacturing, retail, and other industries that power the physical world.

The opportunity ahead is much larger than any single workflow or vertical. We're building the infrastructure for AI to operate reliably inside the real world.

The Role

As Product Manager, AI Agents, you'll define what it means for an AI operator to be truly excellent at operational work.

This isn't a role focused on adding AI features to an existing SaaS product.
AI is the product.

Relay has to understand an incoming problem, reconstruct context scattered across multiple systems, interpret company-specific rules, determine the right next action, use tools to execute it, recognize when something has gone wrong, know when human judgment is necessary, and carry the work through to a measurable outcome.

And it has to do this in environments where the end user may be a logistics coordinator, warehouse operator, customer service representative, dispatcher, buyer, or operations manager, not an AI expert.

You'll own the product systems and experiences that make those agents intelligent, trustworthy, controllable, and increasingly autonomous.

This is a senior individual contributor role for someone who wants to help define a new category of software from first principles.

What You'll Own

Define how BackOps agents work

Own product strategy across the agent lifecycle: how agents understand work, reason about it, take action, handle ambiguity, recover from failure, learn from outcomes, and collaborate with humans.

You'll help answer fundamental questions such as

• What context does an agent need to make the right decision?
• Which parts of a workflow should be deterministic and which should be agentic?
• When should an agent act autonomously versus request approval?
• How should agents interpret SOPs, business rules, historical outcomes, and unstructured information?
• How should an a

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nability, or trust had meaningful real-world consequences.

• Worked in logistics, manufacturing, commerce, construction, healthcare, field services, or another operationally complex industry.
• Built for users who aren't highly technical and have little patience for software that requires them to change how they work.
• Developed products where software interacts with both digital systems and real-world operational processes.

You don't need to arrive knowing supply chain.

You do need to be the kind of product builder who can become dangerous in a complicated domain very quickly.

This Probably Isn't the Role for You If

• Most of your AI experience is adding a chatbot or generative feature to an otherwise traditional SaaS product.
• You think the objective is to maximize autonomy rather than maximize customer outcomes.
• You prefer product problems where behavior can be completely specified in advance.
• You stay primarily at the roadmap/PRD layer and expect engineering or research to make the difficult AI product decisions.
• Your first instinct is to replicate a customer's existing workflow exactly as it exists today.

Why BackOps

AI has become remarkably good at generating information.

The next frontier is much harder: AI that can be trusted to do the work.

In the physical economy, that means more than producing the right answer. An agent has to understand what's happening, make a decision, interact with real systems, navigate exceptions, communicate with real people, and remain accountable until the problem is actually resolved.

That creates an unusually rich product problem.

You'll help determine how agents reason about real-world operations, where humans remain in the loop, how quality is measured, how trust is earned, and how AI progresses from assisting an operator to owning an outcome.

Few product teams get the opportunity to define those interaction models while the category itself is still being invented.

That's the opportunity at BackOps.