AI Architect / Engineer (Agentic AI & LLM Architecture)

As our AI practice scales, we are seeking an experienced AI Architect / Engineer to act as the senior technical authority shaping how we design and deliver next-generation AI solutions. This is a role for someone who has moved beyond building individual models to architecting entire systems: agentic platforms, LLM-powered applications, and the production infrastructure that makes them dependable at enterprise scale.

You will sit at the intersection of strategy and delivery, operating across multiple client engagements simultaneously. In the early phases you will shape solutions, validate technical approaches, and translate ambiguous business problems into robust, deployable architectures. As engagements mature, you will provide the technical oversight that keeps delivery teams aligned to the original design intent. Your influence will be felt in pre-sales conversations, solution blueprints, and the technical standards that define how our practice builds.

This is a hands on architectural role, not a purely advisory one. We expect you to remain close to the code, to prototype where it accelerates a decision, and to set a credible technical example for the engineers and data scientists you guide.

Required skills & experience:

• Lead end-to-end solution architecture for AI and LLM-based systems, spanning data, integration, infrastructure, and deployment.
• Design agentic architectures and multi-agent orchestration patterns, defining how LLMs, tools, APIs, and retrieval layers interact reliably.
• Shape early-stage engagements (scoping, solutioning, estimation, and pre-sales) turning client ambition into deliverable technical plans.
• Provide technical validation and quality oversight across several concurrent projects, mitigating risk before it reaches delivery.
• Define LLM integration and prompting strategies, including RAG, fine-tuning, evaluation, and guardrailing approaches.
• Establish MLOps and LLMOps practices that ensure solutions are observable, testable, and production ready.
• Set architectural standards, reusable patterns, and reference implementations that raise the quality bar across the practice.
• Partner with Responsible AI colleagues to embed safety, security, and governance into solution designs from the outset.

To qualify for this role, you must have:

• Minimum 5 years in AI architecture or AI engineering, ideally 10+, with a track record of production deployments.
• Deep expertise in LLMs, agent frameworks (e.g. LangGraph, AutoGen, Semantic Kernel), API design, and orchestration.
• Strong cloud engineering experience.
• Proven MLOps / LLMOps capability — CI/CD for models, monitoring, evaluation, and cost optimisation.
• Hands-on software engineering background (Python and modern tooling) underpinning your architectural decisions.