Sr. AI Engineer – Agentic Systems

Senior AI Engineer, Agentic Systems The Role As a Senior AI Engineer on agentic systems you'll own the agent architectures that put our models in front of business users, and the work of making them reliable enough to stay there. Design, agentic behaviour, and performance optimization are all inherent to the role, because the needs converge: architecture shapes behaviour, and behaviour determines what needs optimizing. What makes it interesting is what the agents have to do. Underwriting, claims, and the other core areas each involve multi-step workflows with real consequences, so agents need to reason over long context, follow complex instructions reliably, and integrate with systems of record that were never designed for them. Reliability is the hard part, and it is largely an evaluation problem rather than a prompting one. This work is aimed at direct implementation. People on this team move between agentic work, systems engineering, and applied science as priorities shift. Less a multi-agent system than one generalist with broad tool access. Major Responsibilities * Design and develop agentic systems end-to-end: agent loop design, orchestration, memory and state, tool integrations, and multi-agent workflows * Make agents reliable: diagnose why a loop stalls, why a tool gets misused, or why behaviour drifts between runs, and design the guardrails that hold up under real traffic * Measure agent quality continuously rather than at demonstration time: evaluation sets that reflect real workflows, regression checks that catch behavioural drift, and analysis that explains a failure rather than only flagging it * Tune the tradeoffs that decide whether an agent is usable: latency, answer quality, and token cost, including the judgement of which to give up in a given workflow * Integrate agents with the systems and data they depend on, and carry them from prototype to something the business can rely on in production

Design and develop end-to-end agentic systems, including loop design, orchestration, and tool integrations. Ensure agent reliability through continuous evaluation, performance tuning, and robust guardrails for production environments.

Requires deep expertise in production Python and experience building agentic systems with frameworks like LangGraph or Claude Agent SDK. Candidates must demonstrate strong systems fundamentals, evaluation rigor, and the ability to manage tradeoffs in latency and token costs.

• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Python
• Agentic Systems
• LLM Orchestration
• System Architecture
• Performance Optimization
• Evaluation Frameworks
• LangGraph
• Claude Agent SDK
• Distributed Systems
• Event-driven Systems
• Kafka
• Retrieval Systems
• Memory Management
• Full-stack Development
• Software Engineering
• Workflow Management
• Multi-Agent Systems
• Artificial Intelligence
• Applied Science
• Systems Engineering
• Underwriting

• Technology
• Software
• Engineering
• Data & Analytics
• Finance & Accounting
• Artificial Intelligence Engineer
• Artificial Intelligence Engineer (General)
• Software Developers

Minimum experience

5+ years

Posting language

English

Working hours

40 hours per week