Sr. Software Engineer, GenAI

About Us

Instrumentl is a hypergrowth YC-backed startup with over 4,000 nonprofit clients, from local homeless shelters to larger organizations like the San Diego Zoo and the University of Alaska. We are building the future of fundraising automation, helping nonprofits to discover, track, and manage grants efficiently through our SaaS platform.

About the Role

As a Sr. Software Engineer, GenAI at Instrumentl, you’ll own the full lifecycle of AI features—from rapid prototyping to production deployment and ongoing evaluation. You will build agentic LLM systems that can plan and use tools, implement RAG pipelines over our domain data, manage and evolve embeddings and indices, and stand up evaluation/observability so our AI is grounded, safe, and cost‑effective.

What you will do

• Design agentic systems & ship AI to production: Turn prototypes into resilient, observable services with clear SLAs, rollback/fallback strategies, and cost/latency budgets. Build tool‑using LLM “agents” (task planning, function/tool calling, multi‑step workflows, guardrails) for tasks like grant discovery, application drafting, and research assistance.
• Own RAG end‑to‑end: Ingest and normalize content, choose chunking/embedding strategies, implement hybrid retrieval, re‑ranking, citations, and grounding. Continuously improve recall/precision while managing index health.
• Collaborate cross‑functionally while raising engineering standards: Work side by side with Product, Design, and GTM on scoping, UX, and measurement; run experiments (A/B, canaries), interpret results, and iterate. Write clear, maintainable code, add tests and docs, and contribute to reliability practices (alerts, dashboards, incident response).

What we're looking for

• Software engineering background: 7+ years of professional software engineering experience, including 1+ years working with modern LLMs (as an IC). Startup experience and comfort operating in fast, scrappy environments is a plus.
• Hands-On: you’ve used Python (FastAPI or equivalent) PostgreSQL or any relational language, Redis etc, and you’re open to adopting new tools to get the job done.
• Data chops: Comfortable with SQL, schema design, and building/maintaining data pipelines that power retrieval and evaluation.
• Infrastructure & languages: Proficiency in Python (FastAPI, Celery) and TypeScript/Node; familiarity with Ruby on Rails (our core platform) or willingness to learn. Experience with AWS/GCP, Docker, CI/CD, and observability (logs/metrics/traces).
• LLM agentic systems: Experience building tool/function‑calling workflows, planning/execution loops, and safe tool integrations (e.g., with LangChain/LangGraph, LlamaIndex, Semantic Kernel, or custom orchestration).
• Collaborative approach: You thrive in a cross‑functional environment and can translate research ideas into production-ready solutions.