Software Engineer II - Python

Minimum Qualifications

• Master's degree in Computer Science, Software Development, Machine Learning, or a related field, or 3‑5+ years of production‑level engineering experience.
• 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 bridging research code and production software.

• Hands‑on experience with Agent Core runtime for building and managing autonomous agents.
• Extensive experience using Lang Graph 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 product ionizing Data Science models, transforming research‑grade code into high‑performance, scalable APIs (e.g., FastAPI).
• Experience with the full MLOps lifecycle: model deployment, versioning, and performance monitoring.
• Familiarity with Amazon Sage Maker or other cloud‑based ML platforms.
• Expertise in the AWS ecosystem:
  Lambda (Serverless), Step Functions, ECS/EKS (Containers), Event Bridge, and S3.
• Strong proficiency in Infrastructure as Code using Terraform.
• Experience building asynchronous, event‑driven architectures.
• Proficiency in Splunk and Cloud Watch for production monitoring and alerting.
• Strong knowledge of 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.

• Design and implement autonomous agents using Agent Core and orchestrate them via Lang Graph 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 newest technologies, frameworks, and AI research papers to the team; early adopters of tools to improve velocity or service quality.
• Build and maintain 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 Lang Graph for agent‑specific visibility and Splunk for broader system health.
• Participate in rigorous code reviews and help define engineering standards for the Data Science team.
• Collaborate to derive technology solutions that meet evolving business needs with limited specifications.

This role may include participation in an on‑call rotation to support production systems and ensure service reliability. On‑call responsibilities may include coverage during nights and weekends, with frequency and scheduling determined by team needs and communicated accordingly.

Our team members receive competitive compensation, health benefits, and other perks to support life and well‑being. We offer a full suite of benefits and perks tailored to our staff.

Decisions related to employment are not based on race, color, religion, national origin, sex, physical or mental disability, sexual orientation, gender identity or expression, age, military or veteran status or any other characteristic protected by state or federal law. The company provides reasonable accommodations to qualified individuals with disabilities in accordance with applicable state and federal laws. Applicants requiring reasonable accommodations in completing the application and/or participating in the application process should contact a member of the Human Resources team, at