Staff Engineer

Our client is building an AI-native revenue platform designed to eliminate busywork and amplify sales performance. The product is a collective intelligence layer that transforms messy, real-world data into actionable context for autonomous AI agents enabling sales teams to spend less time digging through dashboards and more time moving pipelines forward.

This is a high-impact opportunity to define what AI-native software looks like. You'll help build the orchestration and context layers that power agentic systems, working closely with product and GTM teams to deliver measurable outcomes. If you thrive in fast-paced environments and want to shape the future of intelligent software, this is the place to build.

What You'll Do

• Build the context graph: Ingest and unify data from multiple sources (CRM and beyond) into a semi-structured graph with strong tenant isolation.
• Orchestrate agentic systems: Design planner/executor patterns and policies that turn context into content and actions.
• Deliver where users work: Expose capabilities through native surfaces (apps, chat, integrations) with tight product loops.
• Prove outcomes: Define success metrics (e.g., tasks auto-completed, pipeline lift) and wire observability for rapid iteration.
• Balance cost & reliability: Tune agent performance for accuracy, latency, and cost; design fallbacks and safeguards.

What Were Looking For

• 4+ years of post-graduation experience building and owning backend/platform systems end-to-end (excluding internships).
• Strong Python backend development skills and experience standing up cloud infrastructure.
• Experience stitching messy, multi-source data into usable product context.
• Product-oriented mindset with a bias for action and clear decision-making under ambiguity.
• Curiosity, ownership, and a willingness to get hands dirty in a fast-paced startup environment.

Nice to Have

• Exposure to agent orchestration, planning systems, retrieval/graph-shaped context, or eval frameworks.
• Experience with distributed systems at scale.

Important Notes

• Candidates must have established professional experience in the U.S. post-graduation.
• H1B transfers are accepted, but new sponsorships are not.
• Compensation expectations should align with early-stage startup norms, not big tech benchmarks (e.g., L6 at Shopify).

What We Value

• Motivation to join a startup and contribute meaningfully to its mission.
• Awareness of the product vision and how your skills can drive impact.
• Realistic expectations around compensation, equity, and growth in a lean, high-ownership environment.