The posting
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, Agent Platform, you'll own the product foundation that makes Relay extensible, reliable, secure, and increasingly reusable across customers, systems, and workflows.
BackOps operates in environments that were never designed for AI. A single workflow might span an ERP, a carrier portal without an API, an email inbox, a PDF attachment, a customer-specific business rule, and a human approval before anything can move forward.
Making an agent work once is not the hard part.
The hard part is building a platform that makes the next integration easier, the next workflow faster to launch, the next customer less bespoke, and thousands of concurrent resolutions more reliable than the humans and systems they replace.
You'll own that problem.
You'll work at the intersection of product architecture, enterprise infrastructure, agent execution, customer deployments, and developer experience. You'll partner closely with engineering, our founders, and customers to identify where recurring complexity should become a durable platform primitive, and where it shouldn't.
This is a senior individual contributor role with extraordinary leverage. You won't inherit a mature roadmap. You'll help define the product architecture BackOps scales on.
What You'll Own
Build the platform underneath every AI operator
Own the strategy and roadmap for the core capabilities that allow Relay to connect, reason, execute, recover, and scale across enterprise environments.
That may include:
Integrations, connectors, APIs, webhooks, and data movement Browser automation and interaction with non-API systems Workflow execution and orchestration primitives Identity, credentials, permissions, and access controls Agent tooling, configuration, and extensibility Execution state, retries, recovery, and exception handling Observability, auditability, and production monitoring Testing and evaluation infrastructure Internal and external developer tooling Enterprise security, governance, and deployment controls
Turn deployments into product leverage
Our customers have complicated environments. That complexity is a source of product insight, not a reason to build fifty different versions of BackOps.
You'll work closely with engineers, designers, members of our GTM team, and our customers to understand what we're repeatedly solving, identify the right abstraction, and turn deployment patterns into reusable capabilities.
You'll continually answer questions like:
What belongs in the core platform versus a customer-specific implementation? Which integrations should we build natively, make configurable, or enable others to extend? Where should we create an abstraction, and where would an abstraction create more complexity than it removes? How do we reduce the marginal engineering effort required to launch the next customer, workflow, system, or vertical?
Make enterprise AI reliable enough to run operations
Our agents don't just surface information. They take action.
You'll define the product requirements and operating standards that make that possible at enterprise scale: reliability, latency, isolation, permissions, traceability, error recovery, governance, and security.
You'll partner deeply with engineering on technical tradeoffs and make sure those decisions connect back to customer value.
Create a world-class builder experience
The people building on BackOps should be able to create sophisticated workflows without understanding every piece of infrastructure underneath them.
You'll define the primitives, interfaces, APIs, tools, and product surfaces that make the platform powerful without making it unnecessarily complicated.
Define what scale actually means
You'll establish the metrics that tell us whether the platform is compounding:
Time to launch a new integration or workflow Deployment and configuration time Reuse across customers and use cases Execution success and recovery rates Platform reliability and performance Engineering effort per incremental deployment Adoption of shared platform capabilities
The goal isn't simply to ship infrastructure. It's to make every additional BackOps deployment easier because the previous ones existed.
What We're Looking For
You may be a strong fit if you:
Have 6+ years of relevant experience across product management, engineering, founding, or similarly technical product-building roles, with meaningful ownership at the Senior or Staff level. Have built platform, infrastructure, API, integration, workflow, developer, or similarly technical products used in production. Have exceptional technical fluency. You don't need to be the person writing the production code, but you can go deep with engineers on architecture, APIs, distributed systems, state, data models, permissions, reliability, and system tradeoffs. Have repeatedly turned ambiguous or customer-specific problems into simple, reusable product abstractions. Understand that great platform product management requires customer obsession, not distance from the customer. Have operated in a high-growth environment where the architecture had to evolve while the company continued shipping. Can move fluidly between long-term platform strategy and the detailed product decisions required to make it real. Have strong opinions, loosely held. You can create clarity with incomplete information, explain your reasoning, and change your mind quickly when the evidence changes. Hold an unusually high bar for product quality while still moving with urgency.
Particularly Compelling
We'd be especially interested if you've:
Built products at a breakout AI company or exceptional B2B software company where platform leverage mattered to company scale. Worked on agent infrastructure, workflow automation, integration platforms, developer platforms, enterprise infrastructure, or AI/ML systems. Built products that must interact with messy third-party or legacy systems rather than operating inside a pristine software ecosystem. Worked in logistics, manufacturing, commerce, construction, healthcare, field services, or another industry where software touches the physical world. Built technology for users who are exceptionally good at their jobs but aren't necessarily technical, and shouldn't have to become technical to use your product.
Domain expertise in supply chain is useful. However, exceptional product judgment and technical depth matter more.
This Probably Isn't the Role for You If
Your definition of platform product management is primarily maintaining an internal engineering backlog. You need a fully formed roadmap before you can start executing. You're most comfortable optimizing an established product rather than defining abstractions that don't yet exist. You prefer staying several layers removed from customers and deployments. You default to solving every new requirement with either a one-off build or a generalized framework. Great judgment about when to productize is fundamental to this role.
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.
