Python AI Engineer: Agentic AI & MLOps

Rocket; Detroit (MI); On-site; USD 140,000 - 190,000; Full time

Job summary

Rocket Close is seeking an experienced Python AI Engineer to lead the creation of Agentic AI systems and productionize ML models within our Data Science/AI Platform. You will push the boundaries of cloud-native AI, collaborating with data scientists and leveraging AgentCore and LangGraph for orchestrated, observable workflows.

You will stay at the forefront of the field, researching new technologies and applying them to scalable, high‑availability services on AWS.

Qualifications

• Master's degree in CS/ML or equivalent professional experience (3–5+ years).
• Expert-level Python for distributed, cloud-native services.
• Experience bridging research to production in DS/ML environments.

Responsibilities

• Design autonomous agents using AgentCore and orchestrate with LangGraph for visibility.
• Partner with Data Scientists to productionize ML models in AWS environments.
• Research and prototype new AI tools and frameworks to improve velocity and quality.
• Build and maintain cloud-native infrastructure for AI/ML inference (AWS).
• Implement deep monitoring and alerting with LangGraph and Splunk.
• Contribute to engineering standards and rigorous code reviews.
• Collaborate with teams to translate vague concepts into precise specs.

Skills

Python expert

Distributed systems

Cloud-native services

Data science in production

ML productionization

Agile methods

Education

Master's degree or equivalent

Tools

AgentCore

LangGraph

AWS (S3, Lambda, Step Functions)

Terraform

FastAPI

SageMaker

Splunk

CloudWatch

Job description

Rocket Close is seeking an experienced Python AI Engineer to lead the creation of Agentic AI systems and productionize ML models within our Data Science/AI Platform. You will push the boundaries of cloud-native AI, collaborating with data scientists and leveraging AgentCore and LangGraph for orchestrated, observable workflows.

You will stay at the forefront of the field, researching new technologies and applying them to scalable, high‑availability services on AWS.