LLM / GenAI Engineer
Scale.jobs
Location
🇺🇸 United States
Type
full_time
Salary
Undisclosed
Posted
3w ago
Job Description
About The Role
The role
is focused on architecting and scaling production-grade generative AI features, moving beyond basic API wrappers to build robust, deterministic systems powered by large language models. The engineer will design orchestration layers, optimize retrieval-augmented generation (RAG) workflows, and implement strict evaluation and guardrail systems to ensure safety, accuracy, and low latency at scale. The team works at the intersection of modern software engineering and applied AI. This role involves collaborating with backend engineers and product owners to integrate intelligence into core platform workflows, ensuring LLM applications are observable, cost-effective, and highly performant.
Key Responsibilities
- Design and optimize advanced RAG pipelines, utilizing hybrid search, query rewriting, and reranking strategies to maximize retrieval quality.
- Implement systematic LLM evaluation pipelines using frameworks like Ragas, TruLens, or custom LLM-as-a-judge architectures to measure hallucination and accuracy.
- Integrate and manage enterprise-grade vector databases such as Pinecone, Milvus, or pgvector, including indexing strategies and metadata filtering.
- Develop agentic workflows and multi-agent systems using frameworks like LangGraph, Autogen, or custom state machines.
- Deploy, fine-tune, and optimize open-source models (e.g., Llama, Mistral) using LoRA, QLoRA, and quantization techniques for specialized tasks.
- Build robust guardrails and alignment layers using tools like NeMo Guardrails or Llama Guard to ensure safe and deterministic model behavior.