--- title: 'Product Manager, Agent Platform at BackOps-AI' canonical: 'https://feeny.ai/job/product-manager-agent-platform-backops-ai-san-francisco-nzdmr6d526et' type: 'job' last_seen: '2026-10-18' --- # Product Manager, Agent Platform at BackOps-AI - **Company:** BackOps-AI - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-10-05 - **Last confirmed live:** 2026-10-18 - **Apply:** https://jobs.gem.com/backops-ai/am9icG9zdDr0YlA0K66-yObf9LjHJlXZ ## Job description ## 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. ## About BackOps-AI ## Company Overview - **One-liner**: BackOps builds an AI-native operating system for supply chain and logistics operations, turning complex manual workflows into structured, always-on execution across systems and teams. - **Entity Type**: Private (Series A) - **Headquarters**: San Francisco, California, USA - **Founded**: 2024 - **Founders**: Sean McCarthy (CEO) and Henry Ou (CTO) ## Core Business - **Primary industry**: Supply Chain & Logistics Technology / AI Operations - **Target customers**: B2B, Enterprise (automotive manufacturers, global retailers, grocery chains, machinery suppliers, and other logistics-heavy industries) - **Mission statement**: To build the AI-native operating layer for modern operations, turning complex, manual workflows into structured, always-on execution across systems and teams. ## Products & Services - **AI Process Center**: Captures institutional knowledge by recording how employees complete logistics workflows, identifies inefficiencies, and converts those processes into automated actions. Includes a Workflow Recorder and historical ticket mining. - **Relay**: An agentic automation engine that runs continuously across communication channels (email, Slack, portals, etc.) to detect issues and resolve them automatically. Capabilities include order management, claims & disputes, shipping & logistics tracking, accounts payable, data & document processing, and customer support triage. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed - **Total Funding**: $34M raised - **Last Round**: $26M Series A (led by Theory Ventures, with participation from Gradient, Construct Capital, and 10VC) — raised in April 2026 - **Notable Investors/Partners**: Theory Ventures, Gradient Ventures (Google's AI fund), Construct Capital, 10VC - **Growth Signals**: - Raised $26M Series A just 6 months ago (as of Sept 2026) - Customers report 93% faster response times and 100% automatic filing of eligible carrier claims - Clients include one of the world's largest automobile manufacturers, a major global retailer, leading grocery chains, and major U.S. machinery suppliers - Headcount of 25 employees, actively scaling team ## Competitive Advantages - **AI-native architecture**: Not a chatbot bolted onto existing workflows, but a purpose-built "operations OS" that learns processes from SOPs and executes across fragmented systems (web portals, carrier APIs, ERPs, email, Slack) - **Forward-deployed team model**: Works alongside customer operations from day one, mapping processes and tuning decision logic — a hands-on approach that reduces implementation friction - **Founding team depth**: CEO Sean McCarthy was an early hire at Amazon Shipping (global sales); CTO Henry Ou led applied ML teams at Apple and ByteDance and ran an ERP integration business — a rare blend of operational and technical expertise - **Full lineage capture**: All decisions and exceptions are logged with complete context, creating a living system of record for how teams actually work ## Strategic Focus - Scaling the team and accelerating product roadmap to meet growing demand for AI-driven logistics automation - Expanding the platform's ability to handle more complex, multi-departmental workflows (CS, Ops, Finance, Sales) - Deepening integrations with legacy systems, carrier portals, and enterprise tools ## Why Work Here - **Culture**: Emphasizes a "human + machine" philosophy — building tools that augment operators, not replace them. Described as a place for "operators, engineers, or builders who believe that the future of work is human + machine and not human versus machine." - **Remote/Hybrid**: Based in San Francisco with two offices; specific remote policy not detailed publicly, but likely hybrid given the forward-deployed team model. - **Notable perks**: Opportunity to work on a category-defining product in a space ripe for transformation. Small, nimble team (~25 employees) means high impact and ownership. Backed by top-tier investors with deep AI and logistics expertise. - **Engineering culture**: CTO with strong ML background from Apple and ByteDance suggests a high bar for technical excellence. Work involves cutting-edge AI applied to real-world operational problems. ## Sources 1. [backops.ai](https://www.backops.ai/) — Official product and company description 2. [backops.ai/careers](https://www.backops.ai/careers) — Careers page and mission 3. [backops.ai/about-us](https://www.backops.ai/about-us) — Founding story and team 4. [builtin.com](https://builtin.com/company/backops-ai) — Company profile with headcount and founding year 5. [cbinsights.com](https://www.cbinsights.com/company/backops-ai) — Funding data, news, and Expert Collections ## Other roles at BackOps-AI - [AI/ML Engineer](https://feeny.ai/job/ai-ml-engineer-backops-ai-san-francisco-tyxgw1w8m2q2) — San Francisco, CA - [Product Manager, AI Agents](https://feeny.ai/job/product-manager-ai-agents-backops-ai-san-francisco-85gwkqvw6apn) — San Francisco, CA - [AI GTM Strategy Manager](https://feeny.ai/job/ai-gtm-strategy-manager-backops-ai-san-francisco-a4hrkkk6s97r) — San Francisco, CA - [Engineering Manager, Infrastructure and Security](https://feeny.ai/job/engineering-manager-infrastructure-and-security-backops-ai-san-francisco-e4cky54xn1np) — San Francisco, CA - [Engineering Manager, Core Product Engineering](https://feeny.ai/job/engineering-manager-core-product-engineering-backops-ai-san-francisco-h95knyk3tvwm) — San Francisco, CA - [Technical Program Manager](https://feeny.ai/job/technical-program-manager-backops-ai-san-francisco-5t082nnrpj11) — San Francisco, CA - [Product Security Engineer](https://feeny.ai/job/product-security-engineer-backops-ai-san-francisco-5f1syczeyyn6) — San Francisco, CA - [Founding GTM Recruiter](https://feeny.ai/job/founding-gtm-recruiter-backops-ai-san-francisco-trwn25fwpbnn) — San Francisco, CA - [Enterprise Account Executive](https://feeny.ai/job/enterprise-account-executive-backops-ai-los-angeles-6x74mdhyy05s) — Los Angeles, CA - [Enterprise Account Executive](https://feeny.ai/job/enterprise-account-executive-backops-ai-chicago-vkd5te1sf1mq) — Chicago, IL