AI Large Language Model (LLM) Technology Architect

26 ott - Monza
Accenture

Overview

As an hands-on AI/LLM Architect, you design and implement enterprise AI systems spanning classical ML, generative AI, and agentic architectures. You translate requirements into concrete designs, build components, and produce ADRs and diagrams to guide engineers. You work with cross-functional teams to Ground AI outputs in enterprise data, while balancing performance, cost, and reliability.

This role offers hands-on engineering, architecture ownership, and a path toward higher architectural leadership.

Responsabilità

- Design and deliver end-to-end software components for AI architectures
- Build AI agent architectures, prompts, tools, and memory systems
- Develop agent orchestration patterns with robust state management and error handling
- Evaluate design options to balance capability, cost, performance, and reliability
- Create evaluation strategies measuring accuracy, relevance, faithfulness
- Integrate foundation models via fine-tuning, RAG, and custom integration
- Develop AI context layer with ingestion, context graphs, and knowledge grounding
- Implement embedding, vector storage, and retrieval in RAG pipelines
- Design memory components for grounded, accurate outputs




- Create reusable components and templated patterns for delivery acceleration
- Optimize model usage, latency, throughput, and cost
- Ensure systems meet security, governance, and Responsible AI standards
- Build observability, logging, tracing, monitoring, and cost tracking
- Produce architecture artifacts (ADRs, blueprints, diagrams) for teams
- Collaborate with data engineers, ML engineers, and application developers
- Continuously learn new patterns and tools to stay enterprise-grade

Requisiti fondamentali
- Proven experience designing and deploying enterprise-grade AI solutions with agentic, generative, and classical AI/ML on at least one cloud vendor
- Hands-on experience in agentic, LLM, and Generative AI space
- Strong Python programming skills
- Solid foundation in architecting and operationalizing LLM-driven architectures
- Professional experience coding, ML, DL, and NLP applications
- Several years as a machine learning architect delivering large-scale data and analytical systems
- Collaboration with cross-functional teams
- Analytical and problem-solving mindset
- Communication of complex architectures clearly
- Python
- LLM architectures
- Agentic and generative AI

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