Software Engineer, AI/ML, GenAI

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Instrumentl

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2016

🤝 Sem Fins Lucrativos

⚡ Produtividade

☁️ SaaS

💰 Seed Round em 2017-07

Non-profit • Productivity • SaaS

A Instrumentl é uma plataforma abrangente de gerenciamento de subsídios que simplifica o processo para ONGs, consultores de subsídios e universidades descobrirem, se inscreverem e gerenciarem concessões. Oferece um vasto banco de dados com mais de 400. 000 financiadores e mais de 20. 000 subsídios selecionados para ajudar os usuários a encontrar rapidamente as melhores oportunidades de financiamento. A Instrumentl também aprimora a redação de subsídios com tecnologia de IA, automatiza prazos, gerencia tarefas e fornece ferramentas para colaboração e gestão de documentos. Confiada por mais de 4. 000 ONGs, a Instrumentl já facilitou mais de $ 1 bilhão em subsídios ativos, apoiando uma série de missões críticas.

Descrição

• 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. • Manage embeddings at scale: Select, evaluate, and migrate embedding models; maintain vector stores (e.g., pgvector/FAISS/Pinecone/Weaviate/Milvus/Qdrant); monitor drift and rebuild strategies. • Fine‑tune & build evaluation: Run SFT/LoRA or instruction‑tuning on curated datasets; evaluate the ROI vs. prompt engineering/model selection; manage data versioning and reproducibility. Create offline and online eval harnesses (helpfulness, groundedness, hallucination, toxicity, latency, cost), synthetic test sets, red‑teaming, and human‑in‑the‑loop review. • 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).

🎯 Requisitos

• Software engineering background: 5+ years of professional software engineering experience, including 2+ years working with modern LLMs (as an IC). Startup experience and comfort operating in fast, scrappy environments is a plus. • Proven production impact: You’ve taken LLM/RAG systems from prototype to production, owned reliability/observability, and iterated post‑launch based on evals and user feedback. • 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). • RAG expertise: Strong grasp of document ingestion, chunking/windowing, embeddings, hybrid search (keyword + vector), re‑ranking, and grounded citations. Experience with re‑rankers/cross‑encoders, hybrid retrieval tuning, or search/recommendation systems. • Embeddings & vector stores: Hands‑on with embedding model selection/versioning and vector DBs (e.g., pgvector, FAISS, Pinecone, Weaviate, Milvus, Qdrant).IDocument processing at scale (PDF parsing/OCR), structured extraction with JSON schemas, and schema‑guided generation. • Evaluation mindset: Comfort designing eval suites (RAG/QA, extraction, summarization), using automated and human‑in‑the‑loop methods; familiarity with frameworks like Ragas/DeepEval/OpenAI Evals or equivalent. • 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). • Data chops: Comfortable with SQL, schema design, and building/maintaining data pipelines that power retrieval and evaluation. • Collaborative approach: You thrive in a cross‑functional environment and can translate researchy ideas into shippable, user‑friendly features. • Results‑driven: Bias for action and ownership with an eye for speed, quality, and simplicity.

🏖️ Benefícios

• 100% covered health, dental, and vision insurance for employees, 50% for dependents • Generous PTO policy, including parental leave • 401(k) • Company laptop + stipend to set up your home workstation • Company retreats for in-person time with your colleagues • Work with awesome nonprofits around the US. We partner with incredible organizations doing meaningful work, and you get to help power their success.