AI Native Associate Director

Accenture Italia; Napoli; Sur place; EUR 85 000 - 153 000; Plein temps

Résumé du poste

Accenture Italia seeks an AI Engineer (Agentic/Applied) to design, build, and deploy production-grade agentic AI systems across enterprise stacks. You will collaborate directly with client teams, lead technical design sessions, and create scalable patterns and accelerators for broad engagements.

The role emphasizes hands-on deployment of agentic AI solutions, production-grade engineering, and leadership in architectural governance within enterprise environments.

Qualifications

• Proven production-grade software engineering in AI environments.
• Experience with deploying multi-agent systems in production.
• Strong backend & cloud-native engineering skills.

Responsabilités

• Architect and govern production-grade agentic systems at enterprise scale.
• Define RAG pipeline standards and quality benchmarks.
• Set multi-LLM integration standards across providers.
• Own LLMOps including eval strategy, governance and observability.
• Lead senior client engagements and align leadership with delivery teams.
• Publish reusable patterns, accelerators, and engineering standards.
• Define metrics for agentic system quality and report business impact.
• Demonstrate production software engineering experience.
• Hands-on deployment of agentic AI solutions in production.
• Experience with agentic orchestration frameworks (e.g., LangGraph, CrewAI, AutoGen).
• Call LLM APIs in production code with proper abstractions and cost controls.
• Own embeddings, chunking, vector databases, and context engineering in RAG pipelines.
• LLMOps fundamentals: eval harness design and prompt versioning.
• Cloud-native maturity: Kubernetes, Docker, microservices, CI/CD, IaC.
• Strong Python; Java or equivalent; production debugging and observability.
• Lead and develop engineering teams.

Connaissances

Python

Java

LLMOps

LLM APIs

Kubernetes

Docker

LangGraph

CrewAI

AutoGen

Outils

OpenAI API

Vertex AI

Description du poste

Role Description

You build the systems that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent system in production, you have owned the eval harness, and you know what happens when your agent fails at 2 am because you have lived it.

As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements.

This role sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.

Key Responsibilities

• Architect and govern production-grade agentic systems at enterprise scale: multi-agent orchestration across complex environments, RAG pipelines, policy-based routing, memory management, and programme-level lifecycle observability
• Define RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure metric-backed tradeoff decisions are documented and transferable
• Set multi-LLM integration standards: vendor-agnostic architecture by default, fallback routing and cost governance as standard design practice across providers including OpenAI, Anthropic, Vertex AI, and open-source models
• Own LLMOps at programme scale: eval strategy, prompt governance, observability tooling standards, safety monitoring and cost controls across multiple concurrent systems
• Lead client engineering engagements at senior level — facilitate architecture design sessions, lead proof-of-concept delivery, and drive alignment between client technology leadership and delivery teams
• Shape and publish reusable patterns, accelerators, and engineering standards that scale across the practice and reduce ramp-up time on new client engagements
• Own the measurement framework for agentic system quality: define accuracy, latency, safety, and cost metrics; present programme-level AI impact in business terms to senior client stakeholders.
• Demonstrable and extensive experience of software engineering experience in production environments
• Hands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiable
• Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level
• Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs
• RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering
• LLMOps fundamentals: eval harness design, prompt versioning, and production observability
• Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)
• Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience
• Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure
• People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations.

Compensation at Accenture

Compensation at Accenture varies depending on a wide array of factors including but not limited to role, level, seniority, responsibility, skillset, and level of experience. For this position, the Dirigente National Collective Bargaining Agreement applies, with one of the following pay grades and corresponding gross annual salary range:

Dirigente: 85,000 - 152,500 EUR