Sr. Backend Engineer

We are tackling a surprisingly unsolved yet critical problem for the $1T chemical manufacturing industry: “what products from my portfolio can I sell into this account”?

A manufacturing salesperson sells hundreds or thousands of SKUs into tens of thousands of manufacturing accounts. To answer the question of what to sell where requires many hours of deep research or in-depth discussion with the customer directly. It also requires either deep chemistry expertise or decades of experience in the space.

Corvus is solving this: by combining agent-powered research workflows with a proprietary, homegrown dataset of US manufacturers, we give our clients understanding about what each one makes, which chemistries go into making it, and how that maps onto a customer's specific portfolio.

That visibility unlocks workflows the industry has never had. Reps find cross-sell opportunities inside accounts they've serviced for years. Sales leaders prioritize markets product by product instead of by gut. Companies see their penetration at the SKU level rather than the account level.

Our confidence in our vision is reflected in our traction: we've 6x'd our revenue, 3x'd our customer count in the last six months, and our initial customers have all renewed and expanded. We work with the largest chemical distributors and manufacturers, and we’re looking to double down for our next phase of growth.

You'll be the senior backend engineer at Corvus, working directly with the two cofounders every day. There's no PM layer: you'll hear the customer's problem firsthand, decide what it means for the system, and own the work from design through shipping and watching how it behaves in production.

Your work will be the foundation of the product. Corvus runs on a growing body of data about manufacturers, facilities, products, and people. Your job is to design the systems and data model around it so that this data stays correct and consistent as it grows, and so that agents and research workflows can build and iterate on top of it. You'll own the architecture decisions that determine what we can build next, and how we scale for our next phase of growth.

Some exciting technical opportunities you'll face:

• Build the knowledge graph for an industry. The clean, current map of data points across hundreds of thousands of manufacturers doesn’t exist. You’ll design the data model that turns all of it into one coherent, queryable picture, providing an unprecedented level of insight and actionability for an entire sector of the economy.

• Make agents the primary users of our platform. Our agents write most of the data and read most of it. There’s no established playbook for this; we will be living on the frontier and defining what “best-in-class” looks like.

• Scale the system while the ground is still moving. We’re going from a handful of customers to many. You’ll make the calls on what to build now and what to defer, at the stage where those decisions compound most.

Who we're looking for

• 6–10 years of professional software engineering experience, with deep relational database expertise (preferably Postgres) and strong TypeScript or Python.

• You've designed a canonical data model that lived through real change (new data sources, new entity types, merges and splits) and you can talk concretely about what you'd do differently.

• You've built or owned entity resolution, deduplication, or reconciliation logic, and you understand the tradeoffs between deterministic rules, probabilistic matching, and human review.

• You've built resiliency into systems: queues, retries, idempotency, observability.

• You use AI tooling as a core part of how you build, and you're curious about how data should be structured for agents to work with it. You don't need to be an AI engineer, but the stack shouldn't be foreign to you.

• You're pragmatic about scale. You know what not to build yet, and you can explain your reasoning in plain terms to people who'll push back.

• You want to talk to customers. Our best technical decisions have come from an engineer hearing a customer explain what they'd do next.

• You're excited about working in person with the team in NYC, 5 days a week.

• Traction. 10x growth over the past year

• Architectural ownership. The data layer is the asset the company is being built on, and you'll be the one who designs it.

• Lean team, high agency. Small team, high bar we set for ourselves, and systems that go from your branch to production without intermediaries.