Salary / Hourly Rate: $100,000 - $200,000 per year
Benefits: Open to considering relocation for the right candidate but really prefer local candidates,Candidates should already be based in US
Role Information
Role Overview: N/A
Responsibilities: Create the collective memory: Ingest and unify multi-source data into a multi-level context graph with strong tenant isolation., Orchestrate agentic systems: Design planner and executor patterns, tools, and policies that transform context into actionable content and build lightweight evaluation harnesses., Deliver where users work: Ship native surfaces and integrations within apps, chat, and GTM tools in collaboration with Product and Sales teams., Prove outcomes: Define metrics such as tasks auto-completed and adoption rates, and wire observability for rapid ship-learn-iterate cycles., Balance cost and reliability: Tune for accuracy, latency, and cost while implementing fallbacks and safeguards for real-world loads.
Qualifications: 4+ years of experience in building and owning backend or platform systems with measurable business impact., Strong proficiency in Python and ability to establish cloud infrastructure and production services., Experience in integrating messy, multi-source data into product-ready models with sound reliability, privacy, and multi-tenant boundaries., Possess product thinking, a bias to ship, and comfort making decisions with approximately 70% of information.
Minimum Requirements: 4+ years building and owning backend/platform systems end-to-end,Strong proficiency in Python,Experience with cloud infrastructure and production services,Experience with data integration and reliability management,Product-oriented thinking with a bias to ship,Has not applied directly to the company before.
Screening Questions: Walk me through a 0→1 platform or data system you owned end-to-end. What were the trade-offs, and how did you instrument outcomes?,How would you model a tenant-safe context graph from CRM, product usage, and third-party data?,Hybrid location (KO): Which office can you work from 3 days/week — San Francisco, New York City, or Vancouver? If relocating, what’s the timeline?,Work authorization (KO): Do you currently have work authorization for that location (US or Canada) without sponsorship?
Company Information
About Company: N/A
Culture: N/A
Additional Information
Interview Process: 2-3 interviews and technical assessment with the team + founders. Initial screening by VP of Engineering.
Day to day: Days 0–30: Stand up ingestion paths, define the context-graph MVP, wire observability + eval harness, and ship one end-to-end agent flow to a pilot user., Days 31–60: Harden multi-tenant boundaries, expand planner/executor tools & policies, add 1–2 key integrations (e.g., CRM, sales tools), and review metrics weekly with Product/Sales., Days 61–90: Tune latency/cost and add fallbacks, document runbooks, establish basic SLAs/on-call for agent pipelines, and iterate based on adoption and task-completion data.
Team: Report directly to the founders (CEO/eng lead) on a small, senior, high-ownership team. You’ll partner daily with Product and closely with Sales/RevOps, with decision-making authority over architecture, tooling, and shipping priorities; cadence includes a daily stand-up and a weekly design/growth review.Work alongside a small, senior, high-ownership founding team reporting directly to the Founders (CEO/Eng lead).
Growth: Meaningful equity ownership and the chance to shape the company’s technical direction from day one. Clear paths to Founding Staff/Tech Lead, owning major platform surfaces, and—if desired—helping hire and mentor the next wave of engineers while setting standards for reliability, security, and developer velocity.
Ideal Candidate Profile: Early engineer from an AI/data/infra or GTM-tooling startup; comfortable owning a platform surface and taking it from 0→1→reliable operation., Strong backend in Python; has stood up cloud services (preferably AWS) and production pipelines; familiarity with FastAPI/GraphQL, Postgres or DynamoDB, Kubernetes, Pulumi, and event-driven patterns., Experience with agentic/retrieval systems or graph-shaped context; has designed planner/executor loops, added evals/observability, and shipped iterative improvements., Sound multi-tenant data modeling, privacy, reliability, and fallback instincts; clear communicator of trade-offs., Product taste: partners with Product and Sales, writes lightweight design docs, and iterates quickly based on metrics., Able to work hybrid 3 days/week from San Francisco, New York City, or Vancouver (or relocate on an agreed timeline).
