Lead I - ML Engineering

About the role

This role is focused on agent systems engineering , not pure model training. The work centers on building the body around the model: tools, connectors, memory, context management, orchestration, evaluation, and controlled execution. Current agent stacks increasingly depend on tool use, session/state handling, tracing, and sandboxed execution rather than model tuning alone.

What you'll do

• Design and build AI agents that automate meaningful end-to-end workflows
• Enterprise connectors and APIs
• Persistent memory and session/state handling
• Orchestration across single-agent and multi-agent flows
• Evaluation, tracing, and guardrails

What you need

• 9–12 years in data science & ai
• Machine learning
• Python
• TypeScript
• LLMs
• System design
• Any graduate

Good to have

• Prototyping