AI Architect / Engineer (Agentic AI & LLM Architecture)

Qualifications

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. 
• Comfort managing multiple engagements at once, with pragmatic judgement on trade-offs and delivery risk. 

Ideally, you’ll also have, but not essential

• Experience in consulting, professional services, or pre-sales environments. 
• Exposure to enterprise-scale, regulated AI deployments (financial services, public sector, healthcare). 
• Familiarity with vector databases, knowledge graphs, and advanced retrieval techniques. 
• Relevant cloud or AI certifications. 

You must be

• Willing to work on client sites, potentially for extended periods.
• Willing to travel for work purposes and be happy to stay away from home for extended periods.
• Eligible to work in the UK without restriction.

#TalanUK #LI-HB1

Additional Information

Compensation & Benefits Package

• BDP Plus – A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.
• 25 days holiday + bank holidays.
• 5 days holiday buy/sell option.
• Private medical insurance.
• Life cover.  
• Cycle to work scheme.
• Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).
• Employee assistance programme.
• Bespoke online learning via Udemy for Business.

Why join

You will be a founding technical voice in a practice that is investing decisively in AI. The work is varied, intellectually demanding, and commercially significant, you will shape solutions that reach production, not slideware. You will have the autonomy to define how we build, the support of a collaborative multidisciplinary team, and a clear platform to grow into a practice-leading technical figure. 

Company Description

Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI).

Job Description

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.