Agentic Engineer

Overview

We re building a modern, cloud-native platform and evolving towards an agentic-first engineering model, where AI agents perform meaningful delivery and operational work alongside a small, highly experienced engineering team.

We re looking for an Agentic AI Engineer to design, build and own the production platform that enables AI agents to operate safely and effectively. This is not simply about integrating LLMs, it is about creating the infrastructure, tooling and governance that allows autonomous systems to deliver real business value in production.

A key part of this role is knowing when an AI agent is the right solution and when a deterministic workflow is the better engineering choice. You ll help define this balance and play a central role in shaping how AI is adopted across the organisation.

• Design, build and own the production platform that enables AI agents to perform real engineering and operational tasks.
• Develop the tooling, orchestration, guardrails, evaluation frameworks and execution patterns required for reliable autonomous systems.
• Make architectural decisions around where agentic AI adds genuine value and where traditional deterministic workflows are more appropriate.
• Build evaluation frameworks for measuring the quality, reliability and safety of non-deterministic AI outputs.
• Work closely with engineering teams to ensure autonomous systems can safely interact with code, infrastructure and business-critical workflows.
• Deliver production-ready AI agents that automate complex engineering and operational processes.
• Help shape and evolve an AI-first operating model across the wider technology function.

You ll work with modern LLMs, agent orchestration frameworks, evaluation tooling, cloud-native infrastructure (AWS or similar), APIs and contemporary AI development ecosystems.

• Proven experience building and operating production-grade agentic AI systems—not just prototypes or prompt engineering demonstrations.
• Strong understanding of agent orchestration, tool design, guardrails and evaluation for non-deterministic systems.
• Experience designing secure autonomous workflows that interact with applications, codebases or cloud infrastructure.
• Excellent judgement around when agentic AI is the right solution versus when deterministic automation delivers a better outcome.
• Strong software engineering and cloud architecture fundamentals.

• Experience working with leading foundation model providers and modern AI development ecosystems.
• Background in applied AI research or LLM experimentation.
• Experience with retrieval systems, RAG, context engineering or knowledge systems.
• Familiarity with cloud-native AI deployment and MLOps practices.