Senior Backend Engineer

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🕒 Junho 26

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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

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• 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.