AI LLM Architect - Manufacturing and Operations (All Genders)

Accenture PLC; Bayern; Hybrid; EUR 95,000 - 150,000; Full time

Benefits offered by this job

Flexible home office options

Access to 30k+ training courses

Certifications and learning platforms

Job summary

Accenture PLC in Germany seeks a hands-on AI/LLM Architect to design and build advanced AI systems across ML, generative AI, and agentic platforms. You will translate requirements into architecture decisions, create reusable components, and produce ADRs, diagrams, and integration specs with cross-functional teams.

The role focuses on enterprise-grade reliability, security, observability, governance, and grounding AI outputs in enterprise data.

Qualifications

• Proven experience designing & deploying AI/ML solutions for enterprise.
• Experience with agentic and generative AI architectures.
• Hands-on coding experience in Python and system integration.

Responsibilities

• Independently design, build, and deliver AI software components end to end.
• Architect AI agent architectures, tools, and memory systems.
• Evaluate design options balancing capability, cost, and reliability.
• Build and validate RAG pipelines with foundation model integrations.
• Produce ADRs, diagrams, and integration specifications for teams.

Skills

Bachelor’s Degree

AI/ML architect experience

Agentic / LLM / Generative AI

Python coding

Education

Bachelor’s Degree or equivalent

Job description

Your Mission

At Accenture, you shape the environment in which you thrive – with ways of working that suit you. You stay flexible and become part of a team full of unique individuals who make a difference together.

As a hands‑on AI/LLM Architect, you will be at the heart of designing and building advanced AI systems that power the modern enterprise. This is a deeply technical, hands‑on role — you will spend the majority of your time in the architecture and engineering of real‑world AI solutions across classical machine learning, generative AI, and agentic systems, delivering these within active client engagements. You will translate requirements into concrete architecture decisions: selecting design patterns, evaluating and benchmarking technical frameworks, assembling reusable components, and making deliberate technology choices that balance innovation with enterprise‑grade reliability. You will design and build AI agent architectures — including multi‑agent orchestration, tool use, skills use, and memory systems — and work hands‑on with foundation models through fine‑tuning, retrieval‑augmented generation (RAG), and custom model integration. A part of your work will also involve engineering the AI context layer that makes these systems intelligent in practice — connecting enterprise knowledge bases, structured and unstructured data sources, and domain‑specific content so that AI outputs are grounded, accurate, and relevant to the client’s business. You will design and validate systems against enterprise non‑functional requirements across security, observability, governance, performance, and scalability. A core output of this role is the production of tangible engineering and architecture deliverables. This means writing and owning software components — building, integrating, and testing AI system modules as a practitioner — alongside producing detailed architecture artifacts including architecture decision records (ADRs), component diagrams, data flow diagrams, and integration specifications that guide and enable broader engineering teams. You will work with cross‑functional delivery teams alongside data engineers, ML engineers, and application developers, and this role is an opportunity to develop deep expertise across the full AI architecture stack, sharpen your engineering instincts on complex, real‑world problems, and build a foundation for growing into a lead or principal architect over time.

Your Daily Work

• Independently design, build, and deliver software components across the AI architecture — owning them end to end from design through implementation, integration, and testing as a hands‑on practitioner
• Design and build AI agent architectures — including individual agents, their prompts, tools, and skills, multi‑agent orchestration, and memory systems — making deliberate design pattern and technology choices
• Design and implement agent orchestration patterns that handle task handoffs, communication, state management, and error recovery, validating them through hands‑on prototyping
• Evaluate multiple design options and technical approaches, making deliberate, justified design choices that balance capability, cost efficiency, performance, and enterprise‑grade reliability
• Design, build, and run evaluation strategies and harnesses that measure agent and system quality on metrics such as accuracy, relevance, and faithfulness, translating findings into design improvements
• Architect and implement foundation model integrations — selecting the right models, invocation patterns, and customization approaches (fine‑tuning, RAG, custom integration) based on capability, cost, and performance trade‑offs
• Design and build model adaptation and fine‑tuning pipelines, applying working knowledge of transformer‑based architectures to inform model selection and optimization
• Design and build the AI context layer — including context graph design and ingestion pipelines that parse, chunk, enrich, and index structured and unstructured enterprise content, and the retrieval components that ground AI outputs in the client’s knowledge
• Build embedding, vector storage, and retrieval (semantic, hybrid, reranking) into end‑to‑end RAG pipelines, applying integration patterns that connect to enterprise data sources
• Design and implement context assembly and memory components that manage prompts, context windows, and conversational state for grounded, accurate outputs
• Identify, design, and build reusable components and solution patterns that accelerate delivery and can be templated across engagements
• Design for cost efficiency and performance — optimizing model usage, inference patterns, caching, and resource utilization to meet target latency, throughput, and cost objectives
• Design, build, and validate systems against enterprise non‑functional requirements — implementing guardrails, prompt‑injection defenses, PII handling, and access controls for security and Responsible AI
• Build governance controls including versioning, audit logging, and lineage tracking, and produce the model documentation that keeps systems auditable
• Build observability into systems — logging, tracing, monitoring, alerting, and cost tracking — to ensure AI solutions remain healthy, performant, and scalable in production
• Produce detailed architecture artifacts — including architecture decision records (ADRs), architecture blueprints, design documents, agent orchestration and integration pattern specifications, component and data flow diagrams — that guide and enable broader engineering teams
• Continuously learn, evaluate, and apply new design patterns, frameworks, and technologies across the fast‑evolving AI landscape, balancing innovation with enterprise‑grade reliability
• Collaborate with cross‑functional delivery teams — data engineers, ML engineers, and application developers — to translate requirements into concrete architecture decisions that meet stakeholder needs

Who You Are

• Bachelor’s Degree or equivalent
• Proven experience in designing & deploying AI / ML solutions using at least one cloud vendor as an AI/ML architect.
• Experience in the Agentic, LLM and Generative AI space, preferably within the manufacturing and operations industry
• Professional experience architecting and operationalizing LLM driven application architecture patterns.
• Practical experience in coding and engineering, machine learning, deep learning and NLP solutions and applications. Coding experience using python

What We Offer

• Flexible working models including home office
• Access to more than 30,000 technical and soft‑skills training courses
• Certifications and learning platforms

The Accenture Culture: Here, YOU are the catalyst for change

Your unique combination of skills, personality, and aspirations sets you apart. When distinct talents, strengths, and perspectives merge, the result is nothing short of extraordinary: ideas that propel the world forward. This is why we champion diversity and personal development at Accenture. Create a working environment where you truly thrive; with responsibilities that resonate deeply; with a workload that is perfectly aligned with your capabilities; and methods that are tailored to your objectives. How you wish to connect, further your development, and personally evolve rests in your hands. This is your career. We are mere facilitators, helping you shape it exactly as you envision.

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent‑and innovation‑led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Visit us at www.accenture.com

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