Senior Backend Engineer

Instrumentl

1d • $175,000 - $220,000

About The Position

Instrumentl is a profitable, hypergrowth, YC-backed SaaS platform building the operating system for grant-funded organizations. More than 5,500 nonprofits use Instrumentl to discover, track, and win grant funding, from local community organizations to the San Diego Zoo and the University of Alaska. Collectively they’ve moved over $1 billion through our platform. We're growing more than 40% year over year, customers love us (Ellis PMF 60+), and we're hiring people who want to build something that matters. This role will own AI features end to end, from rapid prototype to production and the evaluation that keeps them honest. You'll build the APIs, tool-using agents, and RAG pipelines that turn frontier LLMs into grant discovery, application drafting, and research tools our 5,500+ nonprofits rely on every day. It's a high-ownership seat on a small team, where what you ship reaches customers fast and you help shape how we build AI here.

Requirements

• 7+ years building and shipping production backend systems in Python (FastAPI, Celery, or equivalent), taking features from prototype to production with real reliability practices like tests, observability, and rollback.
• Hands-on experience building LLM features in production: tool and function calling, multi-step agent workflows, and the guardrails and evals that keep them grounded, safe, and cost-effective.
• Strong data fundamentals: SQL, schema design, and building pipelines that power retrieval and evaluation.
• Thrives in a fast, scrappy startup environment with high ownership and a bias for action, speed, quality, and simplicity.

Nice To Haves

• TypeScript and Node, plus familiarity with Ruby on Rails (our core platform) or a willingness to learn it.
• Experience with AWS or GCP, Docker, CI/CD, and observability (logs, metrics, traces).
• RAG depth: document ingestion, chunking and windowing, embeddings, hybrid search (keyword plus vector), re-ranking, and grounded citations.
• Experience with re-rankers and cross-encoders, hybrid retrieval tuning, or search and recommendation systems.
• Evaluation mindset: designing eval suites (RAG/QA, extraction, summarization) using automated and human-in-the-loop methods, with familiarity with frameworks like Ragas, DeepEval, or OpenAI Evals.
• Orchestration frameworks: LangChain or LangGraph, LlamaIndex, Semantic Kernel, or custom orchestration.

Responsibilities

• Ship AI to production
• Build tool-using LLM agents (task planning, function and tool calling, multi-step workflows, guardrails) for grant discovery, application drafting, and research assistance.
• Turn prototypes into resilient, observable services with clear SLAs, rollback and fallback strategies, and cost and latency budgets.
• Stand up evaluation and observability so our AI stays grounded, safe, and cost-effective.
• Write high-quality, thoroughly tested code across the backend and the data pipelines that power retrieval and evaluation.
• Contribute to reliability practices: alerts, dashboards, and incident response.
• Partner with Product, Design, and GTM on scoping, UX, and measurement.
• Run experiments (A/B, canaries), interpret results, and iterate.
• Raise engineering standards through clear, maintainable code, tests, docs, and thoughtful review.

Benefits

• 100% covered health, dental, and vision insurance for employees (50% for dependents)
• Generous PTO, including parental leave
• 401(k)
• Company laptop and home-office stipend
• Bi-annual company retreats

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed