Senior Generative AI Engineer: RAG & LLM Production Lead

Dover; San Francisco (CA); Hybrid; USD 150,000 - 170,000; Full time

Benefits offered by this job

Unlimited PTO

Generous parental leave

Entrepreneurial culture

Open management

Small teams impact

Medical coverage

Job summary

Cogniify is seeking a hands-on Generative AI and LLM Engineer in San Francisco to design, build and deploy production-grade AI applications. You’ll own solutions end-to-end, combining strong Python backend development with practical LLM knowledge, vector databases, API integrations, Docker, and cloud platforms.

You’ll design scalable LLM-powered apps, build RAG pipelines, and develop AI-agent workflows while collaborating with product and engineering teams.

Qualifications

• Bachelor’s or Master’s degree in CS/engineering or equivalent practical software development experience.
• 6-9 years of professional software development experience with strong Python.
• Experience building backend services and integrating REST APIs.
• Hands-on experience building LLM or Generative AI applications.
• Practical experience implementing RAG using embeddings, semantic search and vector databases.
• Experience with LangChain, LangGraph, LlamaIndex or a comparable LLM application framework.
• Experience integrating foundation models via APIs (OpenAI, Claude, Gemini, Azure OpenAI).
• Working knowledge of vector databases (Pinecone, Weaviate, Milvus, Qdrant, Chroma, FAISS, pgvector).
• Docker and cloud deployment (AWS/Azure/GCP).
• Understanding of prompt engineering, hallucination reduction, output validation and LLM evaluation.
• Strong software engineering practices, Git, testing and debugging.
• Ability to communicate technical solutions to both technical and non-technical stakeholders.

Responsibilities

• Design and develop scalable LLM-powered applications in Python.
• Build RAG pipelines with embeddings, vector databases and semantic search.
• Develop AI-agent workflows with tool calling, memory and orchestration.
• Integrate LLMs with internal systems and external APIs.
• Evaluate foundation models for accuracy, latency and cost.
• Improve prompt quality, retrieval accuracy and latency.
• Implement safety guardrails and access controls.
• Build automated evaluation frameworks for quality and reliability.
• Containerize apps with Docker and deploy on AWS/Azure/GCP.
• Monitor model performance and production usage (LLMOps).
• Collaborate with product and engineering teams to turn requirements into solutions.
• Document architecture, decisions, APIs and operating processes.

Skills

Python

LLM

Vector DBs

API integration

Docker

Cloud platforms

LLMOps

Prompt engineering

Git

Testing

Education

Bachelor's or Master's in CS/Engineering

Tools

LangChain

LangGraph

LlamaIndex

Transformers

PyTorch

Kubernetes

Job description

Cogniify is seeking a hands-on Generative AI and LLM Engineer in San Francisco to design, build and deploy production-grade AI applications. You’ll own solutions end-to-end, combining strong Python backend development with practical LLM knowledge, vector databases, API integrations, Docker, and cloud platforms.

You’ll design scalable LLM-powered apps, build RAG pipelines, and develop AI-agent workflows while collaborating with product and engineering teams.