Senior AI Agent Engineer — Build Multi-Agent Workflows

Machine Learning Technologies, LLC; California; On-site; USD 170,000 - 230,000; Full time

Job summary

Machine Learning Technologies, LLC in California seeks an experienced AI Agent Engineer with strong backend software engineering skills to build and deploy production-grade AI agents and agent-powered applications.

You will design and implement multi-agent workflows, orchestrate tools, manage state and retries, and integrate agents with internal platforms and external APIs, while upholding reliability through tests, CI/CD, and monitoring.

Qualifications

• 7+ years of professional software engineering experience, backend and production systems.
• 2+ years building AI agents and agent-powered production apps.
• Experience with LLMs, APIs, agent frameworks, and multi-agent orchestration.
• Strong understanding of system design, data structures, and scalable architectures.
• Ownership of end-to-end solutions from discovery to production support.

Responsibilities

• Design, build, test, and deploy production-grade AI agents and automations using LLM APIs and agent frameworks.
• Build multi-agent workflows to automate complex business processes and coordinate tasks.
• Develop backend services, APIs, integrations, and data models for agent-powered apps.
• Integrate AI agents with internal platforms and external tools via APIs.
• Implement evaluation frameworks, guardrails, retries, and human-in-the-loop workflows.
• Follow software engineering best practices including CI/CD, testing, monitoring, and reviews.

Skills

Python backend development

LLM APIs integration

Agent orchestration

Multi-agent workflows

API design

System design

Communication

Ownership mindset

Tools

FastAPI

Git

CI/CD

Docker

PostgreSQL

Job description

Machine Learning Technologies, LLC in California seeks an experienced AI Agent Engineer with strong backend software engineering skills to build and deploy production-grade AI agents and agent-powered applications.

You will design and implement multi-agent workflows, orchestrate tools, manage state and retries, and integrate agents with internal platforms and external APIs, while upholding reliability through tests, CI/CD, and monitoring.