AI Large Language Model (LLM) Technology Architect (All Genders)

Accenture DACH; Wien; Vor Ort; EUR 48.000 - 59.000; Vollzeit

Benefits dieser Stelle

Work on cutting-edge AI

Continuous learning and certifications

Flexible working models

Zusammenfassung

Accenture is seeking an AI Large Language Model (LLM) Technology Architect in Austria to lead hands-on design and delivery of enterprise-grade AI solutions. You will architect agent-based systems, integrate foundation models, and ensure security, observability, and governance across projects.

The role emphasizes practical engineering, ADRs, data flows, and scalable architectures. Collaborate with data and ML engineers to turn client requirements into robust AI platforms that balance innovation

Qualifikationen

• Proven experience in designing & deploying enterprise grade AI solutions using agentic, generative and classical AI/ML on at least one cloud vendor.
• Experience in Agentic, LLM and Generative AI space.
• Proficient in Python.
• Strong foundation in architecting and operationalizing LLM-driven AI architectures.
• Professional experience in coding engineering, ML, DL and NLP solutions and applications.
• Several years hands-on as a machine learning architect designing big data and large-scale analytical engineering solutions.

Aufgaben

• 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
• 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, balancing capability, cost efficiency, performance, and reliability
• Design, build, and run evaluation strategies that measure agent and system quality on metrics such as accuracy, relevance, and faithfulness
• Architect and implement foundation model integrations — including fine-tuning, RAG, and custom integration
• Build embedding, vector storage, and retrieval into end-to-end RAG pipelines connecting to enterprise data sources
• Design and implement context assembly and memory components for grounded outputs
• Identify and build reusable components and patterns for templated delivery
• Design for cost efficiency and performance, optimizing model usage and latency
• Design, build, and validate systems with guardrails, PII handling, and access controls
• Build governance controls including versioning, audit logging, and lineage tracking
• Build observability into systems with logging, tracing, monitoring, and cost tracking
• Produce architecture artifacts (ADRs, blueprints, diagrams) to guide teams
• Continuously learn and apply new AI design patterns across the landscape
• Collaborate with cross-functional teams to translate requirements into architecture decisions

Kenntnisse

AI/ML architecture

Python

Agentic AI

Generative AI

LLM architectures

Cloud integration

Ausbildung

Bachelor's Degree

Jobbeschreibung

AI Large Language Model (LLM) Technology Architect

Career Level: Associate Manager / Specialist

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.

THE 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

EDUCATION

• Bachelor's Degree or equivalent

Basic (required) Qualification

• Proven experience in designing & deploying enterprise grade advanced ai solutions using agentic, generative and classical AI/ML using at least one cloud vendor.
• Practical experience in the Agentic, LLM and Generative AI space.
• Well versed in coding using python
• Solid foundation in architecting and operationalizing LLM driven application architecture patterns.
• Professional working experience in coding engineering, machine learning, deep learning and NLP solutions and applications.
• Several years of hands on experience as a machine learning architect in the industry designing big data, machine learning. large scale analytical engineering solutions.

What We Offer

• Work on cutting‑edge AI, Generative AI, and Agentic AI programmes for leading global organisations.
• Access to continuous learning, certifications, and dedicated development opportunities across cloud, AI, and architecture disciplines.
• Flexible working models and a modern work environment that supports your personal and professional growth.

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.

The annual gross salary for this position starts, depending on qualifications and experience, at €53,600