Senior Backend Engineer - Dealops

Pear VC•Austin, TX

28d

About The Position

Dealops is building the AI-powered revenue optimization and deal pricing platform that modern sales teams rely on to configure, quote, and approve deals with speed and precision. Today, 66% of pricing workflows happen in spreadsheets, costing enterprises millions in lost revenue. We’re fixing this. Backed by $7M from General Catalyst, Pear VC, and operators from Stripe, OpenAI, and Slack, we’ve closed 5- and 6-figure contracts with companies like Plaid and Harvey just 75 days into launch. We're a 7-person team led by ex-Stripe operators, building the GTM Intelligence Platform of the future. We’re looking for an experienced backend engineer to architect and scale the core systems behind the next-generation deal pricing platform. You’ll own critical backend components, including workflow orchestration, pricing engines, AI agent integration, and high-accuracy data infrastructure. This role is ideal for someone who thrives in complexity, values correctness, and enjoys shaping deep technical foundations at an early-stage company.

Requirements

5+ years backend engineering experience
Bachelors Degree in Computer Science or adjacent
Strong proficiency with TypeScript
Strong SQL skills (PostgreSQL or similar)
Experience building complex backend systems with high reliability requirements
History of launching early-stage products end-to-end
Comfortable working closely with customers + solving deeply technical product problems

Nice To Haves

Experience with Express, NestJS, or similar frameworks
Experience with event-driven systems or workflow engines
Knowledge of AI agents, RAG, evaluation models, or production ML
Experience designing internal tooling for high-accuracy workflows
Experience as a tech lead, founding engineer, or working on a lean team

Responsibilities

Architect core backend systems powering deal pricing, modeling, approvals, and workflow automation.
Build scalable services in TypeScript/Node + PostgreSQL to support complex quoting logic, multi-step approval workflows, and real-time decisioning.
Design and extend the workflow engine used by Sales & Finance teams across different customers with highly customizable conditions.
Work closely with Vinay (CTO) to define the long-term systems roadmap across integrations, agents, ingestion systems, and reliability.
Integrate and productionize AI Agents to blend deterministic systems with intelligent automation.
Build admin tooling that leverages natural language and LLMs to reduce onboarding configuration time by 10x.
Own the full lifecycle of features: design → architecture review → implementation → reliability.