Forward Deployed Engineer Manager

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

Descrizione del lavoro

Accenture Italia is seeking a Forward Deployed AI Engineer who will embed with client teams to deploy AI platforms into real enterprise environments. You will own outcomes such as time-to-value, reliability, adoption velocity, and scalability, working across multi-stakeholder settings and across provider stacks.

The role emphasizes translating platform capabilities into measurable business value, leading architecture sessions, and shaping reinvention roadmaps.

Competenze

• Extensive engineering experience with cloud-native systems (APIs, microservices, containerization).
• Deep expertise deploying agentic AI solutions in production.
• Experience with AI platforms (OpenAI, Claude, Vertex AI) and multi-provider pipelines.
• Previous end-to-end delivery ownership in client-embedded environments.

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.
• Lead rapid experimentation to produce production systems within days/weeks across enterprise contexts.
• Architect and govern enterprise AI solutions across the full stack: identity, data, security, governance, platform, and integrations.
• Shape AI reinvention strategy for client executives: value architecture, ROI backlogs, and roadmaps.
• Define and publish reusable reinvention blueprints and accelerators for multiple engagements.
• Lead architecture design sessions, executive workshops, and code-with sessions with client teams.
• Codify delivery learnings and engineering standards to guide future FDE practice.

Conoscenze

AI platform deployments

Cloud-native systems

OpenAI integration

Multi-provider pipelines

Executive communication

Team leadership

Architecture design

Delivery ownership

Strumenti

OpenAI

Claude

Vertex AI

RAG workflows

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.

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