Product Software Engineer II - 1102

The core responsibilities for the job include the following:
Full-stack Development and Implementation:
Implement frontend and backend features supporting AI Core control plane systems, including evaluation dashboards and experimentation workflows.
Develop and maintain APIs that integrate with AI orchestration services and model providers.
Build reusable UI components and backend modules that support internal developer tooling.
Participate in the development of trace visualization and observability surfaces for agent-based workflows.
Backend Integration and AI Workflow Support:
Integrate LLM APIs and support structured agent workflows using frameworks such as LangGraph or similar orchestration tools.
Assist in implementing evaluation and experimentation workflows that promote efficient and responsible model usage.
Debug, optimize, and improve performance of full-stack systems in collaboration with the broader engineering team.
Quality and Operational Support:
Ensure services and applications meet standards for reliability, scalability, and production readiness.
Write unit and integration tests and contribute to CI/CD pipelines.
Participate in code reviews and incorporate feedback to improve implementation quality.
Support monitoring, logging, and operational improvements for AI Core enablement systems.
Collaboration:
Work closely with product, UX, infrastructure, and governance teams to deliver AI tooling aligned with business needs.
Collaborate with U. S. AI Core engineers to implement roadmap-aligned features.
Participate in technical discussions and contribute implementation perspectives and tradeoffs.
Requirements:
2+ years of software engineering experience with backend and frontend development exposure.
Strong proficiency in Python for backend development.
Experience building modern frontend applications using frameworks such as React, Next.js, or similar.
Experience building APIs and working with distributed systems.
Exposure to LLM APIs and agent orchestration frameworks such as LangGraph or similar tools.
Experience contributing to internal tools, developer platforms, or shared services in production environments.
Understanding of CI/CD, automated testing, and modern engineering best practices.
Strong problem-solving skills and ability to work effectively in a collaborative team environment.
Experience with: Full-stack development and internal tooling. Backend APIs and microservices. LLM integrations and workflow-based AI systems.
Frontend frameworks such as React or similar. Cloud environments and production systems.
Bachelor's degree in computer science, engineering, or a related technical field (master's preferred), or equivalent experience.
Preferred Qualifications:
Experience contributing to evaluation tooling or experimentation platforms.
Experience working with observability and monitoring tools.
Experience working in cloud environments such as AWS, GCP, or Azure.
Experience working in globally distributed engineering teams.

Experience
2-4 yrs