Software Engineer, AI/ML GenAI

Job Description Job Description: Software Engineer, AI/ML GenAI Job Overview Job Title Software Engineer, AI/ML GenAI Company Instrumentl Location Remote (US-based candidates required; overlap with Pacific Time Zone hours needed). Concorde, NC and Oakland, CA mentioned as optional office locations. Employment Type Full-Time Compensation & Benefits Salary Range: $175,000 - $220,000 per year (US-based). Equity: Included in compensation package. Health Insurance: 100% covered for employees (50% for dependents). Time Off: Generous PTO policy including parental leave. Retirement: 401(k). Equipment: Company laptop + home workstation stipend. Perks: Company retreats and opportunity to work with nonprofit partners. Key Responsibilities Design and Deploy AI Systems: Build resilient, observable agentic LLM systems (including tool planning, function calling, and multi-step workflows) for grant discovery, application drafting, and document parsing. Own RAG Pipelines: Manage end-to-end Retrieval-Augmented Generation, including content ingestion, chunking strategies, hybrid retrieval, re-ranking, and grounded citations. Manage Embeddings: Select, evaluate, and migrate embedding models; maintain vector stores (e.g., pgvector, Qdrant, Pinecone); monitor drift. Collaboration: Work cross-functionally with Product and Design teams; run experiments (A/B testing); contribute to reliability practices like alerts and incident response. Code Quality: Write maintainable code, add tests and documentation, and ensure cost/latency optimization. Required Qualifications Experience: 5+ years in professional software engineering, with at least 2 years focused on modern LLMs. LLM Agentic Systems: Proven experience building tool/function-calling workflows, planning loops, and safe integrations (e.g., LangChain, LangGraph, LlamaIndex). RAG Expertise: Strong understanding of document ingestion, embeddings, hybrid search, re-ranking, and grounding. Vector Stores: Hands-on experience with embedding model selection/versioning and vector databases (pgvector, Qdrant, Pinecone, Weaviate, Milvus). Evaluation: Experience designing eval suites (RAG/QA, extraction, summarization) using frameworks like Ragas, DeepEval, or OpenAI Evals. Infrastructure: Proficiency in Python (FastAPI, Celery), GCP/AWS, Docker, CI/CD, and observability tools. Data Skills: Comfortable with SQL, schema design, and data pipeline development. Nice to Have Startup experience in fast-paced environments. Familiarity with responsible AI, red-teaming, and domain-specific safety policies. Practical experience with fine-tuning (SFT/LoRA/instruction-tuning). Note: This role supports Instrumentl's mission to drive impact in the nonprofit sector. The company uses AI tools to assist in the hiring process, but final decisions are made by humans.