Talan
AI Architect / Engineer (Agentic AI & LLM Architecture)
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
AI Architect / Engineer (Agentic AI & LLM Architecture)
AI Architect / Engineer
Talan Data x AI is a leading Data Management and Analytics consultancy, specialising in unlocking value and insight from data. We combine cutting-edge Machine Learning (ML) and Artificial Intelligence (AI) to help clients improve operational efficiency through modern processes and technologies.
We are seeking an experienced AI Architect/Engineer to shape the next generation of AI solutions at scale, working at the intersection of strategy and execution.
About the Role
As our AI practice scales, we are looking for a senior technical leader who can architect complex, end-to-end AI and LLM-based systems. This is not a traditional model-building or development role—it is about designing agentic platforms, LLM-powered applications, and production-ready infrastructures that deliver real business impact.
Your responsibilities will span multiple client engagements, where you:
- Drive solution design, technical validation, and delivery oversight from inception to production.
- Translate business challenges into scalable, secure, and high-quality technical architectures.
- Mentor junior engineers, data scientists, and consultants to uphold architectural standards.
- Engage with clients in pre-sales, proposal development, and solution blueprinting.
- Set technical best practices that shape how Talan delivers AI solutions across industries.
This role demands hands-on technical expertise. You should be comfortable building and refining prototypes when needed, aligning technical decisions with real-world business outcomes, and leading with credibility.
Responsibilities
- Lead end-to-end architecture for AI/ML and LLM-based systems, covering data, integration, infrastructure, and deployment.
- Design agentic systems and multi-agent orchestration, ensuring seamless interaction between LLMs, tools, APIs, and retrieval mechanisms.
- Guide pre-sales and solutioning efforts—turning vague business requirements into viable, enterprise-scale technical designs.
- Provide technical oversight across concurrent engagements, mitigating risks and ensuring adherence to design principles.
- Define LLM integration strategies, including:
- RAG (Retrieval-Augmented Generation)
- Fine-tuning and evaluation techniques
- Prompt engineering and guardrails
- Establish MLOps and LLMOps practices, ensuring observability, testability, and production readiness.
- Set architectural standards, reusable patterns, and reference implementations for the practice.
- Collaborate with Responsible AI experts to embed safety, security, and governance into designs from the start.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Required Skills & Experience
To excel in this role, you must have:
- Minimum 5 years (ideally 10+ years) of AI architecture/engineering experience, with a track record of live production deployments.
- Deep expertise in:
- LLMs (e.g., prompt engineering, retrieval, fine-tuning)
- Agent frameworks (e.g., LangGraph, AutoGen, Semantic Kernel)
- API design and orchestration at scale
- Strong cloud engineering experience (AWS, Azure, GCP, or similar).
- Hands-on MLOps/LLMOps proficiency, including:
- CI/CD for model pipelines
- Observability, monitoring, and evaluation frameworks
- Cost optimisation and guardrails
- Robust software engineering background, with expertise in Python and modern tools to underpin architecture decisions.
- Ability to manage multiple high-stakes engagements with tactical judgment on trade-offs and delivery risks.
Ideal (but not essential) Qualifications
- Experience in consulting, professional services, or pre-sales roles.
- Exposure to enterprise AI deployments in regulated industries (financial services, public sector, healthcare).
- Familiarity with:
- Vector databases
- Knowledge graphs
- Advanced retrieval techniques
- AI or cloud certifications (e.g., AWS ML, Azure AI, Google ML).
Get help with your application
Your very own career expert that helps elevate your application to the next level.
What You Need to Bring to Talan
- Willingness to work on-site, potentially for extended periods.
- Comfort with frequent travel and flexible deployment schedules.
- Full eligibility to work in the UK without visa restrictions.
Why Join Talan?
- Join a practice investing heavily in AI—you’ll shape production solutions, not just PowerPoint slides.
- Commercially impactful work with intellectual challenge at every level.
- Build high-quality technical leadership in a collaborative, multidisciplinary team.
- Autonomy in defining processes, alongside clear career growth opportunities.
Compensation & Benefits
| Benefit | Detail |
|---|---|
| BDP+ Promise | Earnable sabbatical (3-month paid) or cash equivalent on progressive steps. |
| Holiday | 25 days (plus bank holidays). Additional 5 days buy/sell option. |
| Medical Insurance | Comprehensive private medical cover. |
| Life Cover | Financial protection for dependents. |
| Cycle to Work Scheme | Up to £2,500 tax-efficient cycle lease. |
| Pension Scheme | 5% employer contribution, salary-sacrificed option. |
| Learning & Development | Full access to Udemy for Business. |
| Support for You | Confidential Employee Assistance Programme (EAP) and expertise networks. |
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills