Accenture
AI LLM Technology Architecture Manager
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior AI/LLM Architect – End-to-End AI Platform Design
This is a critical senior technical leadership position within Accenture’s AI practice, where you will design, lead, and architect enterprise-grade AI platforms that drive business transformation through advanced AI systems. You will operate as a strategic architect at the intersection of AI, business outcomes, and engineering excellence, championing scalable, secure, and observant AI solutions across generative AI, classical ML, and agentic systems.
About the Role
You will serve as the technical visionary for one or more key architecture domains, including:
- Agentic application design (multi-agent orchestration, memory, tooling)
- AI security and trust Foundation
- AI operations (AIOps) and observability
- Data & knowledge engineering (context layer, RAG, fine-tuning)
- Model platforms and scalable inferencing
Your responsibilities will span:
- Defining enterprise-scale AI architectures aligned with business strategy
- Inventing architectures for certified, trust-bound agents—balancing flexibility with governance
- Engineering a "context layer" that bridges structured/unstructured data with semantic precision
- Leading cutting-edge MLOps, FinOps, and FinAIgede security frameworks
- Producing and mentored solutions to production-grade viability
Key Responsibilities
Technical Leadership & Architecture
- Translate business strategy into non-functional requirements (NFRs) (e.g., performance, reliability, cost)
- Lead stakeholder workshops to align on technical feasibility, scope, and expectations
- Decide on build vs. buy AI platforms (e.g., LLMOps tools, foundations models) and technology stacking
- Design model-agnostic multi-agent systems with a central MCP Control Plane
- Own the Agent Registry as the definition-of-truth system + AI Gateway for policy enforcement
- Enforce certification gates to ensure only validated agents enter production (ID, policies, metrics)
- Engineer core agent services:
- First-class semantic memory endpoints (episodic + procedural)
- Inference abstractions, caching, request batching, and performance tuning
- Abstract scalability by architecting end-to-end RAG pipelines with:
- Knowledge graphs, vector embeddings, and semantic memory
- Cost/performance-aware model routing (fine-tuned vs., off-the-shelf)
- Ensure AI governance is by design, enforced through:
- IAM/IAP-bound agent identity + layered security guardrails
- FinOps controls (token budgets, cost-center labelling, alerts)
- Observability as a first-class citizen (OTel, productized metrics)
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.
Delivery & Collaboration
- Design, prototype, and deliver PoCs and foundational reusable architektoni (e.g., memory components)
- Rate ADRs, blueprints, sequence diagrams and specs as primary artifacts
- Mentor cross-functional teams (ML, data, frontend devs) on architectural excellence
- Maintain predictive reference architectures and reusable patterns for scalability
Research & Innovation
- Explore emerging AI tools/patterns to stay ahead
- Adapt AIOps protocols, monetization safeguards, and adaptability protocols
What We Value & You’ll Bring
Must-Have Experience
- Bachelor’s degree or equivalent
- Proven track record designing/building large-scale AI systems in cloud platforms (AWS/GCP/Azure), leveraging:
- Generative AI/LLM agentic systems (multi-agent orchestration, memory abstractions)
- MLOps engineering (ML model lifecycle from inference to deployment)
- Advanced NLP/data engineering (RA hands-on experience sought)
- Python for development/prototyping
Get help with your application
Your very own career expert that helps elevate your application to the next level.
TheiD Experiences Marking
We are looking for senior architects capable of: ✅ Leading -> deep ownership of enterprise AI subdomains (trust/scalability, data context, AIOps) ✅ Balancing radical innovation with enterprise-grade feedback loops ✅ Bridging dev teams and stakeholder expectations through architecture artifacts ✅ Studying industry shifts (AGI, automation cost models) and applying them origin-first reaching
Why Join Accenture?
Accenture was founded on innovation for the future—we deliver ard-legacy value at scale. Here, what you bring changes the world, while you get it all:
- Global Impact: Work with 120+ countries, redefining how industry embraces AI
- Ownership: Leadership-level ownership of platforms, self-steered projects, and architectural communities of practice
- Investment in Your Growth: Mentorship, open access to world-leading experts, and innovation labs—emphasizing that experts here thrive on open problem spaces
- Belong: Diversity as a value, a place where your voice matters, and where our >79K teammates reflect the world’s edge newest
We commit to inclusive potential as mindsets at every level. As one of our senior architects, you’ll accelerate that mission.
Join us here or explore accenture.com/belong for openings like yours.
“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