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Dealops

Founding Engineer

Posted Yesterday
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In-Office
San Francisco, CA, USA
160K-200K Annually
Mid level
In-Office
San Francisco, CA, USA
160K-200K Annually
Mid level
Build and own full-stack features for an AI-powered deal pricing and revenue optimization platform. Responsibilities include developing pricing recommendations, integrating machine learning and rule-based systems, designing A/B pricing experiments, processing natural-language data, building LLM-powered admin tools, incorporating customer feedback, and owning products from design through implementation. The role also supports customer onboarding, project leadership, and future product strategy.
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About Dealops

We’re building the revenue infrastructure the next decade of B2B AI companies run on by starting with the most critical part in the revenue journey, deal pricing. Today, sales reps spend hours building their own pricing spreadsheets for each deal, only to discount too much and spend another cycle iterating with Finance. This is a massive problem for B2B companies, as we’ve seen up to 30% unnecessary overdiscounting with customers. Our founder saw this firsthand when she worked in finance and pricing at Stripe, where she has priced over a thousand deals with the sales org.
This problem exists because pricing is a black box. Sales teams aren’t trained to make pricing decisions and aren’t incentivized to optimize for long-term revenue. As pricing models become more complex due to AI and the shift toward usage-based, outcome-based, and hybrid models, this challenge is only compounding. There’s a massive opportunity to build the revenue infrastructure for next-generation companies.
We’re positioned to lead this market shift as teams are finding out previous solutions are breaking down. That’s why the fastest growing enterprises and AI startups like Airwallex, Plaid, Harvey, LangChain, and Clay are partnering with us to build the foundations of their revenue infrastructure.
Backed by $7M from General Catalyst, Pear VC, and executives from OpenAI, Stripe, Slack, and more, we’re now focused on growing revenue 10x and shaping the future of deal pricing.

The Role

We're looking for a Senior Software Engineer to join our growing engineering team and help build the next-gen AI-powered platform for revenue optimization. You'll work across the full stack -- from our core deal pricing product to the tools that help customers optimize their revenue strategies with data-driven insights. We're a small team, so you'll have plenty of room to fully own high-impact products from day one.

What You'll Do

First 3 months

  • Develop key features for deal pricing and packaging recommendations, blending machine learning with a rule-based engine to optimize pricing.

  • Design and run A/B pricing experiments that directly move customer revenue — past experiments have yielded a 10–20% boost. (Dealops is the first to let companies A/B test rep behavior at scale.)

  • Collect and integrate customer feedback to drive iterative improvement and product-market fit.

By 6 months

  • Build agents that process unstructured, natural-language data to further sharpen our pricing and packaging recommendations.

  • Spearhead infrastructure and tooling for admin users, enabling infinite customization through natural language and LLMs which cuts customer onboarding time by 10x.

  • Contribute to the future product roadmap and our long-term vision of becoming an end-to-end sales optimization platform.

By 9 months

  • Own an entire product or product feature suite, from design through implementation and keep innovating.

Like everyone on the team, you'll also pitch in on customer onboarding and support, and plan and lead projects end-to-end.

What Excites Us
  • 4+ years of software development experience, with a strong full-stack focus (senior preferred; strong mid-level welcome).

  • Proficiency in React, TypeScript, and SQL (PostgreSQL or similar).

  • A track record of building and launching scalable, reliable products in close collaboration with designers and other cross-functional partners.

  • Experience with complex products that have high reliability and accuracy requirements, ideally in a fast-moving environment.

  • Bonus: experience with Tailwind, Express, machine learning, prompt engineering / AI tooling, or previously leading a tech team.

What Excites You
  • Tackle complex, high-impact challenges. Turning pricing from an art into a science is a technically hard, high-stakes problem with enormous room for innovation. AI is at the core of our vision — this year we're building agents that automatically generate quotes for reps and assist managers with approval flows, and that's just the beginning.

  • High ownership and influence. As an early engineer, you'll own large pieces of the product and infrastructure from day one. Your work will shape both our tech stack and our broader product vision, and you'll make genuinely strategic decisions about how pricing software evolves.

  • Fast-paced career growth and leadership. Startups mean accelerated growth. Whether you want to step into a tech lead role, drive product innovation, or architect major systems, you'll be positioned to take on leadership as we scale.

  • Shape company culture. As an early hire, you won't just build the product — you'll help define how we work and what we value. This is a chance to create something special, technically and culturally.

What We Offer
  • Competitive compensation

  • Generous early-stage equity package

  • Unlimited PTO

  • Free meals - lunch and dinner on us.

  • Free ubers for late nights worked in the office

  • Full health coverage

  • Flexible remote time

  • 401K

  • Significant ownership and autonomy

  • The chance to work on cutting-edge AI applications in enterprise software

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