Accenture UK & Ireland
AI LLM Technology Architecture Assoc Manager
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
AI/LLM Architect
As a hands-on AI/LLM Architect, you’ll design and build advanced AI systems for enterprise-scale solutions. This role demands deep technical expertise across classical machine learning, generative AI, and agentic systems, with an emphasis on end-to-end delivery in active client engagements.
Your work will involve translating requirements into robust architecture decisions—selecting frameworks, assembling reusable components, and making strategic technology choices while balancing innovation and reliability. You’ll architect AI agent systems, including multi-agent orchestration, tooling, memories, and fine-tuned foundation models (via RAG, prompt engineering, and custom integrations).
Key responsibilities include designing an AI context layer that connects structured/unstructured enterprise data for grounded, accurate, and business-relevant outputs. You’ll ensure compliance with enterprise non-functional requirements, including security, observability, governance, performance, and scalability.
You’ll own software components end-to-end, from development to testing, and produce detailed architecture artifacts (ADRs, diagrams, integration specs) that guide broader engineering teams. Collaboration with data engineers, ML engineers, and developers is essential.
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.
The Work
Key Responsibilities
- Independently design, build, and deliver AI/ML software components across the architecture stack, owning them from design to production testing.
- Architect multi-agent systems, including:
- Agent orchestration patterns (handoffs, state management, error recovery)
- Tool and skill integration
- Memory systems for conversational context
- Evaluate, prototype, and benchmark design patterns and technologies, balancing capability, cost, performance, and reliability.
- Develop evaluation strategies and frameworks to measure agent/system performance (accuracy, relevance, faithfulness).
- Integrate foundation models via fine-tuning, RAG, and custom pipelines—optimizing for capability, cost, and scalability.
- Engineer contextual AI layers, including:
- Content ingestion, chunking/embedding, and retrieval (semantic/hybrid)
- Memory components for prompts and contextual windows
- Design reusable components and solution templates to accelerate delivery.
- Ensure cost-efficient, low-latency model usage (inference patterns, caching, resource optimization).
- Implement enterprise-grade security & governance:
- Guardrails, prompt injection defenses, PII handling
- Versioning, audit logs, and model documentation
- Embed observability (logging, tracing, monitoring, cost tracking) for production reliability.
- Document architecture via ADRs, blueprints, diagrams, and integration specs.
- Stay ahead of emerging AI patterns and technologies while maintaining enterprise reliability.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Experience
Education
- Bachelor’s Degree (or equivalent technical qualification).
Qualifications & Experience
- Proven ai-ml architect role in cloud environments (AWS/GCP/Azure) for AI/ML solutions.
- Hands-on expertise in generative AI, agentic systems, and LLM-driven architectures.
- Extensive Python engineering in ML/open-source deep learning frameworks.
- Experience building and operationalizing production-grade LLM/agentic systems.
No further formatting tweaks required—this is ready for direct rendering as Markdown.
“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
Location