Enterprise AI Deployment Lead

Accenture Italia; Roma; In loco; EUR 50.000 - 86.700; Tempo pieno

Descrizione del lavoro

Accenture Italia seeks Forward Deployed AI Engineers to implement production-grade AI platforms inside enterprise environments. You will own time-to-value, adoption, reliability, and scalability across multi-stakeholder programs.

Join a team shaping the largest reinvention deployment capability, tackling complex AI problems and driving measurable business value for clients.

Competenze

• Extensive engineering experience with cloud-native systems and AI platforms.
• Proven ability to own end-to-end deployment in production environments.
• Strong leadership and cross-functional team management skills.
• Ability to quantify business value for senior stakeholders.

Mansioni

• Lead enterprise AI platform deployments across complex client environments, owning the full programme from architecture through adoption.
• Own programme-level delivery outcomes: time-to-value, reliability, adoption velocity, and scalability across multiple workstreams with commercial metrics.
• Lead rapid experimentation to produce production-ready systems in days or weeks.
• Architect and govern enterprise AI solutions across identity, data, security, governance, and integration layers.
• Shape reinvention strategy for client executives and build value roadmaps and ROI backlogs.
• Publish reusable blueprints and accelerators that scale across client engagements.
• Lead architecture design sessions and executive workshops with client leadership.

Conoscenze

Cloud-native systems

AI platform deployment

Enterprise delivery leadership

Stakeholder collaboration

OpenAI/Claude/Vertex AI deployment

Strumenti

APIs

Microservices

Containerization

Serverless architectures

Descrizione del lavoro

Role Description

This is not a consulting role. It is not a project delivery role. It is not a research position. A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments. You own outcomes: time-to-value, adoption, reliability, and scalability. Not delivery milestones. Outcomes.

Role Description

This is not a consulting role. It is not a project delivery role. It is not a research position. A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments. You own outcomes: time-to-value, adoption, reliability, and scalability. Not delivery milestones. Outcomes.

The market is beginning to understand what leading technology companies have demonstrated: AI products fail not because the models are weak but because deployment is broken. The gap between a successful AI pilot and an AI capability that scales is bridged by engineers who can translate platform capability into measurable business value inside a real enterprise environment. That is this role.

Forward Deployed AI Engineers form the execution spine of our Reinvention Deployment Engineering pods. We are building the largest FDE capability in the services industry. The engineers who join at this stage will define what the role looks like at scale and will have access to the hardest enterprise AI problems in the market across every industry.

Key Responsibilities

Lead enterprise AI platform deployments across complex multi-stakeholder client environments — Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir — owning the full programme from architecture through adoption

Own programme-level delivery outcomes: time-to-value, reliability, adoption velocity, and scalability across multiple concurrent workstreams, with commercial metrics attached

Lead rapid experimentation at pace: drive ambiguous business problems to working production systems in days or weeks across complex enterprise environments

Architect and govern enterprise AI solutions across the full technology stack: identity, data, security, governance, platform layer, and multi-system workflow integration at programme scale

Shape AI reinvention strategy for client CTO, CFO, and CISO: build value architecture, ROI backlogs, use case prioritisation frameworks, and multi-year AI adoption roadmaps

Define and publish reusable reinvention blueprints, patterns, and accelerators that scale across multiple client engagements and grow the FDE practice

Lead architecture design sessions, executive workshops, and code-with sessions with client engineering and C-suite leadership teams

Codify delivery learnings, failure patterns, and engineering standards that shape the FDE practice and enable the next generation of forward deployed engineers

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 job level is under the A1 National Collective Bargaining Agreement. The gross annual salary range is between 50,000 and 86,700 EUR.

Basic Qualifications

Extensive and demonstrable engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).

Deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.

Extensive and demonstrable experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines.

Extensive and demonstrable experience leading software engineering teams: overseeing delivery, allocating resources across workstreams, and owning the professional development of direct reports"

Demonstrated end-to-end delivery ownership in a client-embedded environment, internal projects, vendor labs, or team-only deployments do not qualify

Proven ability to articulate business value: can quantify the impact of deployments in terms a CFO would recognize and act on

Experience presenting to and building trust with senior client stakeholders, CTO, CFO, or CISO level

Non-linear profiles are expected and welcomed, assessment is based on demonstrated deployment experience and outcome ownership, not CV pattern matching

People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations