Staff / Sr. Staff Software Engineer, GTM AI Brain

DISQO’s mission is to build the world’s most trusted ad measurement platform that fuels brand growth.The world’s largest brands, agencies, and media companies trust DISQO for expert insight and AI-driven intelligence about their advertising performance across all platforms. We capture people’s sentiments and journeys, connecting them with the brands they value and the media they consume. With this identity-based approach, brands gain more accurate and authentic insight so they can create more meaningful interactions.
Joining DISQO Nation means becoming part of a community that champions speed, innovation, and continuous growth. We invest deeply in our talent, empowering our teams to reach their highest potential. Together, we are shaping the future of work at DISQO—defined by performance, purpose, and impact.
We show up each day with curiosity and ambition, committed to learning, accelerating growth, and making a lasting difference. Grounded in our values and principles, we lead and collaborate to elevate performance, accountability, and excellence at every level of the organization. And through it all, we make sure to have fun along the way.

DISQO is hiring a Staff or Sr. Staff Software Engineer to build our GTM AI Brain: the agents, applications, data flows, and automations that change how a modern revenue team operates. You will work alongside our VP of RevOps, who will act as the product manager for this work and own the GTM strategy, priorities, and success metrics. You bring the engineering judgment and the zero-to-one instinct to turn that strategy into systems that ship.

This is a hands-on builder role, operating as an early-stage founding engineer: small surface area, fast cycles, real users (our own GTM team), and direct line to the CTO. You will pick the stack, set the patterns, and put working software in front of sellers, CSMs, and operators every week.

This is not a Salesforce admin role, not a RevOps management role, and not an internal tools maintenance role. RevOps fluency helps, but we are optimizing for engineering depth, product taste, and the ability to operate in ambiguity. Your partner in RevOps brings the domain.

What you will do:

• Build the GTM AI Brain from scratch: agents, copilots, internal applications, automations, and the data plumbing underneath.

• Partner daily with the VP of RevOps to translate revenue workflows (pipeline, forecasting, routing, renewals, expansion, account research, sales prep, CRM hygiene) into shipped software.

• Own the technical architecture end to end: stack choices, data model, integrations, eval harness, observability, and human-in-the-loop patterns.

• Integrate the systems where GTM work lives: Salesforce, Clay, Gong, HubSpot, Slack, Google Workspace, billing, and marketing automation.

• Build reusable patterns for LLM-powered applications: retrieval, tool use, structured outputs, evaluations, permissions, monitoring, and review workflows.

• Use agentic coding tools (Claude Code, Cursor, Codex) as a force multiplier. We expect one engineer with these tools to do what a small team used to.

• Contribute strong technical input into build-vs-buy decisions, with a bias toward reducing SaaS sprawl when we can build something better and faster ourselves.

• Define what "good" looks like through evals before launch, then measure real business impact: productivity, conversion, forecast accuracy, retention, customer experience.

• Set the engineering standards for AI-native GTM systems at DISQO as this capability scales.

What we're looking for:

• 8+ years of software engineering experience building production-grade systems. Track record of shipping, not just designing.

• Zero-to-one builder mindset. You have started something from a blank repo, made the early calls, and gotten real users on it. You are comfortable owning a problem end to end without a team to delegate to.

• Strong fundamentals across APIs, databases, integrations, authentication, permissions, observability, and cloud infrastructure.

• Proficiency with a modern stack: Python, TypeScript, React, Node.js, SQL, and at least one major cloud platform, ideally AWS.

• Hands-on experience building with LLMs: prompt workflows, retrieval, tool calling, structured outputs, evaluations, and agent orchestration. You have shipped something real, not just prototyped.

• A point of view on how agents and AI-native systems change the shape of software. You think in terms of evals, latency, token economics, and failure modes, not just features.

• Strong product judgment. You can take a messy business problem from a non-engineer partner and converge on