Description

You will design and build production-grade multi-agent systems and AI pipelines.

This role is remote.

Responsibilities

• Architect agent orchestration using LangGraph, LangChain, CrewAI, and AutoGen, implementing planning, memory, and reflection patterns.
• Develop and optimize RAG pipelines, including document processing, chunking, embedding workflows, and vector database integration.
• Build agent evaluation, testing, and observability frameworks to ensure production reliability for AI systems.
• Create natural language to data query solutions integrating with Databricks Genie or similar platforms.
• Implement AI guardrails, safety mechanisms, and content filtering while evaluating models for latency and accuracy.

Required Skills

• 6+ years of experience with Python backend development using FastAPI.
• Strong expertise in LLM integration (OpenAI, Azure OpenAI, Anthropic) and open-source models.
• Hands-on experience with RAG architectures, vector databases, and embedding workflows.
• Proficiency in multi-agent frameworks such as LangGraph, CrewAI, or AutoGen.
• Experience with Databricks Genie or similar natural language data query tools.
• Knowledge of prompt engineering strategies, including chain of thought and function calling.
• Familiarity with distributed task processing (Celery), event-driven microservices (Dapr), and real-time streaming (SSE).
• Bachelor’s degree in Computer Science or related field.

Key Skills

Education

Bachelor’s degree