Product Software Engineer

The candidate will have responsibilities across the following functions:

Fullstack 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 visualisation 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, optimise, and improve performance of fullstack 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:

• 5+ 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.

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 with:

• Fullstack 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.

Required Education:

• Bachelor's degree in Engineering, or related technical field (Master's preferred), or equivalent experience.