Autonomous AI Agent Developer

MACHINE LEARNING TECHNOLOGIES LLC; San Jose (CA); On-site; USD 97,000 - 138,000; Full time

Job summary

Agentic AI Developer role at MACHINE LEARNING TECHNOLOGIES LLC in San Jose, CA. Design autonomous AI agents capable of reasoning, planning, and executing multi-step tasks with minimal human input. Integrate LLMs and build agent-based workflows interfacing with enterprise apps, APIs, and external data.

Responsibilities include multi-agent orchestration, RAG-based retrieval, memory, and production-grade monitoring. Requires 5–8 years in software/AI and strong Python + API experience.

Qualifications

• 5–8 years of software/AI experience.
• 2+ years building LLM-based applications.
• Hands-on with AI agents and multi-agent systems.
• Strong Python and API integration experience.
• Experience with RAG pipelines and vector search.

Responsibilities

• Design autonomous AI agents for enterprise apps.
• Build multi-agent workflows for complex tasks.
• Integrate LLMs with APIs, DBs and tools.
• Develop RAG-based apps for contextual retrieval.
• Implement memory, planning, reasoning, and orchestration.
• Create evaluation frameworks for agent accuracy.
• Optimize prompts, latency, and token usage.
• Add monitoring, logging, and security controls.
• Collaborate with data scientists and solution architects.
• Maintain documentation and production deployments.

Skills

prompt engineering

API integration

Python programming

object-oriented design

multi-agent workflows

LLM orchestration

enterprise systems

solution architectures

Education

Bachelor's degree in CS or related

Master's in ML/DS (advantage)

AWS/Azure/GCP GenAI certs (pref)

Tools

Python

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

GPT

Claude

Llama

Pinecone

Weaviate

Chroma

RAG pipelines

AWS Bedrock

Azure AI Foundry

Google Vertex AI

REST APIs

Job description

Agentic AI Developer role at MACHINE LEARNING TECHNOLOGIES LLC in San Jose, CA. Design autonomous AI agents capable of reasoning, planning, and executing multi-step tasks with minimal human input. Integrate LLMs and build agent-based workflows interfacing with enterprise apps, APIs, and external data.

Responsibilities include multi-agent orchestration, RAG-based retrieval, memory, and production-grade monitoring. Requires 5–8 years in software/AI and strong Python + API experience.