Senior Backend Engineer
Job Description
Hello, we’re Instrumentl. 👋 Nonprofits do some of the most important work in the world, and most of them are still managing grants in spreadsheets. We're fixing that. 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 quickly, customers love us (check out our G2 reviews!), and we're hiring people who want to build something that matters.
About the Role
We're hiring a Senior Backend Engineer to 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.What You'll Do
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. Build trustworthy backends 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. Collaborate and raise the bar 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.What We're Looking For
Required 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. This is the core of the role. 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 have 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. Compensation &Benefits
For US-based candidates, the target salary range for this role is 175,000 - $220,000 USD, plus equity. Final compensation is determined based on experience, skillset, scope of responsibility, interview performance, and geographic location. We’re committed to paying competitively and equitably. For candidates based in Canada, compensation varies by province and will be shared by your recruiter early in the process. 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 Instrumentl is evolving rapidly. You’ll always have new challenges and opportunities to grow here. Instrumentl is an equal opportunity employer. We are committed to building an inclusive workplace and do not discriminate based on race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, genetic information, or any other legally protected status. We encourage candidates from all backgrounds to apply. If you need a reasonable accommodation during the application or interview process, please let us know.How to Stand Out
- Showcase end‑to‑end AI backend projects: Build a small, production‑grade microservice that ingests nonprofit data, runs a transformer‑based model to score grant fit, and exposes a REST/GraphQL API. Host the repo on GitHub with clear README, CI/CD pipelines (GitHub Actions or CircleCI), Dockerfile, and a live demo (e.g., on Fly.io). Link this project in your résumé and be ready to walk through architecture decisions, latency optimizations, and how you’d monitor/scale it at Instrumentl.
- Highlight SaaS‑scale backend expertise: In your cover letter and interview, reference concrete experience with the stack Instrumentl likely uses (e.g., Python/Go, PostgreSQL, Redis, AWS/GCP, Kubernetes). Mention specific metrics you’ve improved (e.g., 30 % reduction in query latency, 2× increase in request throughput) and the tooling (SQLAlchemy/ORM profiling, Terraform, Prometheus + Grafana) you used to achieve them.
- Demonstrate GTM‑oriented thinking: The role calls for “GTM” skills, meaning you should be able to translate technical capability into product impact. Prepare a short case study showing how a backend feature you built directly enabled a go‑to‑market initiative (e.g., an API that opened a new partner integration, resulting in X new nonprofit sign‑ups). Quantify the business outcome and be ready to discuss trade‑offs you considered.
- Prepare for Instrumentl’s interview focus: Interviewers will probe for (1) data‑driven decision making on AI model rollout, (2) reliability under rapid iteration, and (3) empathy for nonprofit users. Practice explaining a past failure (e.g., a model that over‑fit) and how you iterated with monitoring, A/B testing, and stakeholder feedback. Bring metrics that illustrate improved grant‑win rates or reduced manual effort.
- Negotiate with hypergrowth, remote benchmarks: Research senior backend salaries for remote U.S. roles at YC‑backed SaaS (typically $180‑$230 k base + 0.1‑0.2 % equity). When discussing compensation, cite comparable offers, emphasize the value you’ll add to AI‑driven product features, and ask for a clear equity vesting schedule and a remote‑work stipend (home office, coworking space, or internet allowance).
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