Software Engineer II - Python

Rocket Companies•Detroit, MI

About The Position

As a Python Engineer on our Data Science team, you will be at the forefront of our most ambitious technical initiatives. Your role is dual-purposed: you will build and orchestrate next-generation Agentic AI systems using AgentCore and LangGraph, and you will act as a Machine Learning Engineer (MLE) to productionize the sophisticated models developed by our Data Scientists. We don't just follow industry trends; we aim to set them. You will be expected to be a perpetual student of the field, constantly researching and implementing the newest technologies to ensure our platform remains world-class.

Requirements

Master's degree in Computer Science, Software Development, Machine Learning, or a related field, OR equivalent professional experience (3-5+ years in production-level engineering).
Expert-level proficiency in Python with a focus on building distributed, scalable cloud-native services.
Proven experience in a Data Science or Machine Learning environment, specifically in bridging the gap between research code and production software.

Nice To Haves

Hands-on experience with AgentCore runtime for building and managing autonomous agents.
Extensive experience using LangGraph to create complex, stateful multi-agent orchestrations with high visibility.
Deep familiarity with Amazon Bedrock, OpenAI, or Anthropic APIs and the latest advancements in LLM reasoning.
Experience building and optimizing RAG (Retrieval-Augmented Generation) pipelines.
Proven track record of productionizing Data Science models, transforming research-grade code into high-performance, scalable APIs (e.g., using FastAPI).
Experience with the full MLOps lifecycle: model deployment, versioning, and performance monitoring.
Familiarity with Amazon SageMaker or other cloud-based ML platforms.
Expertise in the AWS ecosystem: Lambda (Serverless), Step Functions, ECS/EKS (Containers), EventBridge, and S3.
Strong proficiency in Infrastructure as Code (IaC) using Terraform.
Experience building asynchronous, event-driven architectures.
Proficiency in Splunk and CloudWatch for production monitoring and alerting.
Strong knowledge of software development life cycle (SDLC) processes, including unit testing, regression testing, and Agile concepts.
Ability to work with broad, loosely developed concepts and translate them into precise technical specifications.

Responsibilities

Design and implement autonomous agents using AgentCore and orchestrate them via LangGraph to ensure complex workflows are visible and manageable.
Partner with Data Scientists to take ML models from research notebooks into scalable, production-ready AWS environments.
Proactively research, test, and present the newest technologies, frameworks, and AI research papers to the team. You are expected to be an early adopter of tools that can improve our velocity or service quality.
Build and maintain the cloud-native infrastructure (AWS) required for AI/ML inference and agentic execution, ensuring high availability and cost-efficiency.
Implement deep monitoring and alerting for all services, using LangGraph for agent-specific visibility and Splunk for broader system health.
Participate in rigorous code reviews and help define the engineering standards for the Data Science team.
Work without complete specifications to help derive technology solutions that meet the evolving needs of the business.