Senior Backend Engineer

Instrumentl; Fitzgerald; Hybrid; CAD 175,000 - 220,000; Full time

Benefits offered by this job

Health insurance coverage

Generous PTO

Company laptop and home-office stipend

Job summary

Medium is seeking a Senior Backend Engineer to lead the development of AI features for our grant platform. This role focuses on building sustainable backend systems that support our rapidly growing user base. Candidates should have significant experience in backend development using Python and a strong understanding of building LLM features.

We offer competitive compensation, equity, and benefits, including 100% covered health insurance for employees. Join us in making a meaningful impact!

Qualifications

• 7+ years experience in backend systems using Python.
• Experience with LLMs in production, building reliable systems.
• Strong SQL and pipeline-building skills.

Responsibilities

• Build AI features from prototype to production.
• Maintain high-quality code and robust backend systems.
• Collaborate with cross-functional teams to improve UX.

Skills

Production backend systems in Python

Building LLM features

Data fundamentals: SQL, schema design

Startup environment experience

Tools

AWS

Docker

CI/CD

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 more than 40% year over year, customers love us (Ellis PMF 60+), 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.