Sr. Software Engineer, GenAI

The Consensus; Canada; Sur place; CAD 246 000 - 309 000; Plein temps

Avantages offerts par ce poste

Health, dental, vision insurance

Generous PTO

401(k)

Laptop + home-office stipend

Bi-annual retreats

Résumé du poste

Instrumentl is hiring a Senior Engineer for the AI Engineering team to own AI features for grant discovery end to end, from data ingestion to production deployment and evaluation. You’ll work directly with founders and your pod on high-ownership problems in a fast-growing startup.

You will build agentic AI systems, manage data processing pipelines, and own RAG and ranking systems to match grants with nonprofits and foundations, while ensuring safety and observability in production.

Qualifications

• 7+ years of professional software engineering experience with strong Python and DB/schema design skills.
• Hands-on experience building with modern LLMs (at least 1 year).

Responsabilités

• Build agentic AI systems and ship them to production.
• Own RAG end to end: ingestion, embedding, retrieval, ranking, and citations.
• Write clear, maintainable, well-tested code and build reusable components.

Connaissances

Python

Relational databases

CS fundamentals

LLMs (hands-on)

Outils

LangChain

LangGraph

LlamaIndex

Pinecone

Milvus

Rails

AWS / GCP

Description du poste

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:

You'll join our AI Engineering team as a Senior Engineer embedded in one of our product pods, reporting to our AI Engineering Lead. You'll own AI features for grant discovery end to end, from the data backbone that crawls and structures messy source data, through the RAG and agentic systems that match grants to nonprofits, to production deployment and ongoing evaluation. It's a hands-on, high-ownership seat with direct access to founders and real room to grow as the engineering team scales!

What you will do

Build agentic AI systems and ship them to production

• Build tool-using LLM systems that plan, call tools, and run multi-step workflows for tasks like grant discovery, data ingestion, and research assistance.
• Build agentic data-processing pipelines that crawl the web, pull and dedupe messy source data at scale, and structure it into clean, queryable databases other teams build on.
• Turn prototypes into resilient production services with clear fallback, cost, and latency budgets.

Own RAG and ranking end to end

• Own RAG end to end: ingestion, chunking and embedding strategy, hybrid retrieval, re-ranking, citations, and grounding.
• Build ranking and scoring systems that match grants to nonprofits, universities, and foundations using complex relevance techniques.
• Continuously improve recall and precision and keep indices healthy as the dataset grows.

Ship safely and raise the bar

• Stand up evaluation and observability so our AI is grounded, safe, and cost-effective, and treat LLM behavior as non-deterministic by design rather than as a regular API.
• Partner directly with founders and your pod on undefined, complex problems with real autonomy.
• Write clear, maintainable, well-tested code and build reusably so your work expands across teams.

What we’re looking for:

Required

• 7+ years of professional software engineering experience, with deep, recent, multi-year Python and strong relational database and schema design skills.
• Solid CS fundamentals and a demonstrated track record of owning complex systems end to end, from design through production reliability.
• At least 1 year of hands-on experience building with modern LLMs (as an IC).

Nice to have

• Real RAG depth: hybrid search (keyword plus vector), re-ranking or fusion methods, and grounded citations, tuned in production rather than read about.
• Hands-on with at least one of LangChain, LangGraph, or LlamaIndex.
• Vector databases beyond pgvector (Pinecone, Qdrant, Milvus).
• Built end-to-end agentic data-processing systems (crawling, dedup, structuring) with whole-system ownership.
• Evaluation and observability for AI systems: golden datasets, precision vs. recall, LLM-as-judge, and drift monitoring.
• Ruby on Rails (our core platform is on Rails), deep SQL, and experience with AWS or GCP, Docker, and CI/CD.
• Startup experience and comfort operating in fast, scrappy, low-process environments.

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.