The AI Transformation Team focuses on solving complex engineering problems using machine learning and scaling those solutions into real-world applications. Beyond building individual models, we develop agent systems that automate problem solving itself, continuously exploring and improving solutions.
We aim to bridge the gap between research and production by building platforms that apply agentic AI to real-world engineering problems.
Design and build the core infrastructure for the Agent System Framework
Implement key components of the agent runtime, including orchestration, context management, tool execution, and memory abstraction
Collaborate with cross-functional teams to rapidly prototype new agent capabilities and scale them into production systems
Design and improve developer-facing interfaces such as CLI tools and SDKs
Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience
Experience in at least two of the following:
Designing and operating distributed systems or large-scale backend systems
Building and deploying machine learning / AI systems (especially LLM-based systems) in production
Developing agent systems, workflow engines, or orchestration frameworks
Backend development experience in Python, Go, or C++
Master’s or PhD degree in Engineering, Computer Science, or a related field
Proven track record of designing and building agentic AI system frameworks in real-world or large-scale environments
Hands-on experience building LLM-based applications (e.g., tool use, planning, reasoning systems)
Experience building developer tools such as CLI or SDKs
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