Forward Deployed Engineer Manager

Accenture España; Madrid; Presencial; EUR 90.000 - 120.000; Jornada completa

Descripción de la vacante

Accenture España is seeking Forward Deployed AI Engineers who work inside client enterprises to deploy AI platforms, ensure adoption, reliability, and scalability, and own outcomes from architecture to deployment.

This role focuses on bridging AI capabilities with real business value, leading enterprise deployments across multiple stakeholders, and shaping reinvention strategies for CTOs and CISOs, with opportunity to influence the FDE practice.

Formación

• Experience deploying AI platform solutions in enterprise environments.
• Ability to translate platform capabilities into measurable business value.
• Strong leadership of software engineering teams with delivery ownership.
• Experience with multi-provider AI pipelines (OpenAI, Claude, Vertex AI).
• Proven ability to articulate ROI and value to executive stakeholders.
• Comfort leading architecture discussions and executive workshops.
• Non-linear backgrounds welcomed; focus on outcomes and deployment experience.

Responsabilidades

• Lead enterprise AI platform deployments across complex multi-stakeholder 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 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

Conocimientos

Cloud-native systems

Agentic solutions design

AI platforms

Lead software teams

Delivery ownership

Business value articulation

Stakeholder communication

Diverse background welcomed

Descripción del empleo

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

Basic Qualifications

• Strong engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).


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


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


• Strong 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