Ai Native Associate Director

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/8hxikq

Role DescriptionTutti i potenziali candidati sono invitati a leggere con attenzione i seguenti dettagli prima di inviare la propria candidatura.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 ResponsibilitiesArchitect 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 observabilityDefine RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure metric-backed tradeoff decisions are documented and transferableSet 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 modelsOwn LLMOps at programme scale: eval strategy, prompt governance, observability tooling standards, safety monitoring and cost controls across multiple concurrent systemsLead client engineering engagements at senior level — facilitate architecture design sessions, lead proof-of-concept delivery, and drive alignment between client technology leadership and delivery teamsShape and publish reusable patterns, accelerators, and engineering standards that scale across the practice and reduce ramp-up time on new client engagementsOwn the measurement framework for agentic system quality: define accuracy, latency, safety,



and cost metrics; present programme-levelAI impact in business terms to senior client stakeholders.Demonstrable and extensive experience of software engineering experience in production environmentsHands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiableDemonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial levelDirect experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffsRAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineeringLLMOps fundamentals: eval harness design, prompt versioning, and production observabilityCloud-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 experienceQuality 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 exposurePeople lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations. xysqume Compensation at AccentureCompensation 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#J-18808-Ljbffr

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/8hxikq