Autonomous AI Engineer — Enterprise Multi-Agent Systems

Robotic Technologies Automation; San Jose (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Robotic Technologies Automation seeks an experienced AI Engineer to design and deploy autonomous AI agents for enterprise workflows. You will build multi-agent systems with planning, reasoning, and execution capabilities, and orchestrate them using LangGraph, CrewAI, or AutoGen.

Responsibilities include developing RAG pipelines, integrating external tools and APIs, and optimizing latency and scalability while ensuring responsible AI practices.

Qualifications

• 5+ years in software AI/ML engineering or similar.
• Experience delivering agent-based AI workflows in production.
• Strong Python and API integration skills.
• Experience with cloud AI services and scalable architectures.
• Knowledge of security, guardrails, and responsible AI practices.

Responsibilities

• Design autonomous AI agents for enterprise workflows.
• Build multi-agent systems with planning and execution capabilities.
• Implement agent orchestration with LangGraph, CrewAI, or AutoGen.
• Develop RAG pipelines connecting LLMs with knowledge sources.
• Integrate tools, APIs, databases, and services with agents.
• Implement prompt engineering, memory management, and context handling.
• Evaluate agent performance and reliability.
• Collaborate with data scientists and software engineers.

Skills

Python

AI/ML development

LLMs & prompt engineering

RAG architectures

Agent orchestration

REST API integration

Distributed systems

Docker

Kubernetes

Git

CI/CD

Vector databases

Education

Bachelor's degree in CS/AI/DS

Master's in AI/ML/CS

AWS/Azure/Google Cloud AI certs

Tools

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

Pinecone

Weaviate

ChromaDB

FAISS

OpenAI API

Azure OpenAI

AWS Bedrock

Vertex AI

Job description

Robotic Technologies Automation seeks an experienced AI Engineer to design and deploy autonomous AI agents for enterprise workflows. You will build multi-agent systems with planning, reasoning, and execution capabilities, and orchestrate them using LangGraph, CrewAI, or AutoGen.

Responsibilities include developing RAG pipelines, integrating external tools and APIs, and optimizing latency and scalability while ensuring responsible AI practices.