Software Engineer II - Python

Rocket Companies

$90K — $120K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Master's degree in Computer Science, Software Development, Machine Learning, or equivalent experience (3-5+ years in production-level engineering).
  • Expert-level proficiency in Python for developing cloud-native services.
  • Proven experience in Data Science or Machine Learning, bridging research and production software.
  • Hands-on experience with AgentCore for building autonomous agents (preferred).
  • Proficiency with LangGraph for multi-agent orchestration (preferred).
  • Familiarity with Amazon Bedrock or similar APIs (preferred).
  • Experience with AWS infrastructure and Terraform (preferred).

Responsibilities

  • Design and implement autonomous agents using AgentCore and manage them through LangGraph.
  • Collaborate with Data Scientists to productionize ML models into scalable AWS environments.
  • Research and adopt new technologies to enhance platform capabilities.
  • Build and maintain cloud-native infrastructure for AI/ML inference and agent execution.
  • Implement comprehensive monitoring and alerting systems using LangGraph and Splunk.
  • Engage in code reviews and define engineering standards for the team.
  • Translate broad concepts into precise technical specifications.

Benefits

  • Comprehensive health and wellness support for you and your family.
  • Flexible options to support work-life balance.
  • Continuous learning opportunities to enhance professional growth.
  • Access to wellness programs and mental health resources.
Full Job Description
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.

Minimum Qualifications
  • 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.


Preferred Qualifications

Agentic AI & Orchestration:
  • 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.


Machine Learning Engineering (MLE):
  • 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.


Cloud & Infrastructure (AWS):
  • 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.


Observability & Engineering Excellence:
  • 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.


Key Responsibilities
  • Agentic AI Innovation: Design and implement autonomous agents using AgentCore and orchestrate them via LangGraph to ensure complex workflows are visible and manageable.
  • MLE Productionization: Partner with Data Scientists to take ML models from research notebooks into scalable, production-ready AWS environments.
  • Constant Research: 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.
  • System Architecture: Build and maintain the cloud-native infrastructure (AWS) required for AI/ML inference and agentic execution, ensuring high availability and cost-efficiency.
  • Observability: Implement deep monitoring and alerting for all services, using LangGraph for agent-specific visibility and Splunk for broader system health.
  • Code Quality: Participate in rigorous code reviews and help define the engineering standards for the Data Science team.
  • Collaboration: Work without complete specifications to help derive technology solutions that meet the evolving needs of the business.

What you'll get

Our team members fuel our strategy, innovation and growth, so we ensure the health and well-being of not just you, but your family, too! We go above and beyond to give you the support you need on an individual level and offer all sorts of ways to help you live your best life. We are proud to offer eligible team members perks and health benefits that will help you have peace of mind. Simply put: We've got your back. Check out our full list of Benefits and Perks.

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