Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this AI LLM Architect (All Genders) role.
Rezi rewrites your resume against Accenture's job description. Free.
Tailor your resume to this AI LLM Architect (All Genders) role.
Rezi rewrites your resume against Accenture's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the AI LLM Architect (All Genders) posting at Accenture — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the AI LLM Architect (All Genders) posting at Accenture — free, in seconds.
About the Role
As a hands-on AI/LLM Architect, you will design and build advanced AI systems for enterprises. This technical role involves architecture and engineering of AI solutions, including classical machine learning, generative AI, and agentic systems, within client engagements. You will translate requirements into architecture decisions, select design patterns, evaluate frameworks, assemble components, and make technology choices balancing innovation with reliability. You will design AI agent architectures, work with foundation models through fine-tuning and RAG, and engineer the AI context layer to connect enterprise knowledge bases and data sources. You will also design and validate systems against enterprise non-functional requirements like security, observability, governance, performance, and scalability. A key output is tangible engineering and architecture deliverables, including software components and detailed architecture artifacts.
Responsibilities
- 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
Requirements
- Hold a 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
- Minimum B2 Certification in the German Language
Skills
- AI/ML
- AI/ML architect
- Agentic
- LLM
- Generative AI
- machine learning
- deep learning
- NLP
- python
Location
- remote
Work Type
- Flexible working models including home office
Education Level
- Bachelor's Degree or equivalent
Benefits
- Access to more than 30,000 technical and soft-skills training courses
- Certifications and learning platforms
About the Company
- 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
Equal Opportunity
- We are the opinion that no one should be discriminated against because of their differences. All hiring decisions are made independently of age, race, creed, color, religion, sex, nationality, ancestry, disability, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship or any other legally protected status.
- Our great diversity makes us more innovative, competitive, and creative, and helps us to better serve our clients and our communities.