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About the Role

Own the agent architectures that put our models in front of business users, and make them reliable enough to stay there. Design, agentic behaviour, and performance optimization are inherent to the role, as architecture shapes behaviour and behaviour determines optimization needs. This work is aimed at direct implementation, with team members shifting between agentic work, systems engineering, and applied science.

Responsibilities

Design and develop agentic systems end-to-end, including agent loop design, orchestration, memory and state, tool integrations, and multi-agent workflows.
Ensure agent reliability by diagnosing loop stalls, tool misuse, or behavioural drift, and designing guardrails for production traffic.
Continuously measure agent quality using evaluation sets reflecting real workflows, regression checks for behavioural drift, and failure analysis.
Tune tradeoffs between latency, answer quality, and token cost, deciding which to compromise for specific workflows.
Integrate agents with dependent systems and data, and transition them from prototype to production readiness.

Requirements

Experience with agent architectures and making them reliable.
Ability to diagnose and solve problems related to agent loops, tool usage, and behavioural drift.
Experience in designing and implementing evaluation sets for agent quality.
Proficiency in tuning tradeoffs such as latency, answer quality, and token cost.
Experience integrating agents with systems and data.
Ability to carry agents from prototype to production.

Skills

Agent architectures
Agentic systems
Design
Agentic behaviour
Performance optimization
Reasoning over long context
Following complex instructions
System integration
Reliability engineering
Evaluation
Prompting
Systems engineering
Applied science
Agent loop design
Orchestration
Memory and state management
Tool integrations
Multi-agent workflows
Quality measurement
Regression testing
Latency tuning
Answer quality tuning
Token cost optimization

Experience Level

Senior