The chemicals industry is upstream from every product produced around the world. It's a $9 trillion industry that quite literally makes everything else possible. And for the past 50 years, its been run on the same process and technology, resulting in a tremendous amount of open opportunity.
Specifically, in the commercial part of the org, there is no clear understanding of how their portfolio of products/chemicals should be sold into the market. Today it's based on gut, institutional knowledge, and relationships. But, AI uniquely enables us to add quantification around this so we can clearly show which chemicals are used in which end markets and help our customers grow. It's a needle-in-a-haystack problem, solved thousands of times a day, by hand. No modern software has ever really touched it, until now.
That's the problem we exist to solve.
Corvus is a seed-stage startup building AI agents that pair deep chemistry and application knowledge with modern software to transform how this industry sells. We're backed by top industry VCs, led by a CEO who has lived this problem firsthand, and we already have real customers who love what we're building. The market is enormous, critical, and almost entirely underserved. We intend to be the team that finally changes that.
The RoleAs a Founding Engineer, you will be a pivotal member of our product development team, directly responsible for building out the core Corvus platform. You'll sit shoulder-to-shoulder with founders and customers, turn messy real-world pain points into features people actually use, and own core pieces of the platform end to end. Building for this group of users is also fundamentally different than most given how much they are on the road and how they do business.
You will have the opportunity to rethink how the chemicals sector, a critical industry, should operate from the ground up.
What you'll doShip production features across the platform: AI agents, workflow automation, memory architecture, and UI/UX.
Own building the AI agent that powers Corvus across several use cases for Chemical sales teams (and continually adding more)
Take customer feedback and translate it into product functionality
Build integrations for enterprises (Salesforce, Dynamics, custom)
Core part of technical discussions, architecture, and roadmap decisions
Help shape engineering practices, culture, and product direction as part of the early team
Thrive in a startup environment: switching contexts, experimenting, and moving quickly to deliver value without rigid processes
4–8 years of professional software engineering experience.
Experience building with or productizing AI agents
Proficiency across the stack, from React/TypeScript on the frontend to Python on the backend.
Comfortable working in ambiguity, unblocking yourself, and moving quickly to deliver value.
Strong communicator who enjoys collaborating with both technical and non-technical teammates.
Excited about working in-person with the team in NYC (4–5 days/week).
Excited by the challenges and opportunities of an early-stage startup: you’re resourceful, adaptable, and energized by building in fast-moving, sometimes ambiguous situations.
You've built data-heavy or workflow-heavy applications before.
You've been early at a startup and know what that ride actually feels like.
A mission that matters. You'll help modernize an industry that touches nearly everything, and that almost nobody else is fixing.
Direct impact: your work will be in the hands of customers from the start.
Ownership: as an early hire, you’ll have the opportunity to shape not just the product, but also the culture and trajectory of the company.
Growth: whether you want to grow into technical leadership or deepen your craft as an IC, we’ll support your path.
Team: join a small, tight-knit group of founders and engineers who value autonomy, speed, and collaboration.
Salary: Competitive base, calibrated to your experience and location.
Equity: Generous, above-market, we believe you're joining at a pivotal time and should be rewarded for it.
Salary ranges are determined by multiple factors, including the labor market, market compensation bands, internal parity, and budget considerations. The final offer is based on your individual skills, qualifications, location, and experience relative to the role.
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