Forward Deployed Engineer

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

Descripción de la vacante

Accenture is seeking a Forward Deployed AI Engineer who embeds with client teams to deploy and operationalize AI platforms across enterprise environments. You will own production outcomes—time-to-value, reliability, adoption velocity, and scalability—driving measurable business value beyond mere delivery milestones.

You will design and govern AI architectures, translate technical outcomes into CFO-friendly business impact, and help clients scale AI adoption with reusable patterns and

Formación

• Commercial experience designing and deploying AI platforms in production environments.
• Experience deploying cloud-native systems (APIs, microservices, containerization, serverless).
• Strong experience with CI/CD, infrastructure as code, monitoring and debugging.
• Ability to articulate business value of deployments to C-suite.
• Experience presenting to senior client stakeholders (CTO, CFO, CISO).
• Non-linear profiles are welcomed; evaluation based on deployment outcomes.

Responsabilidades

• Embed with client engineering and business teams to deploy and operationalize AI platforms in enterprise environments.
• Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, scalability with business metrics.
• Move from ambiguous problem to production-ready system through rapid experimentation.
• Design and govern AI architectures across the enterprise stack (identity, data, security, governance).
• Translate architecture into business impact and shape use-case roadmaps and ROI backlogs.
• Build reusable patterns, playbooks, and accelerators for the client to own after you leave.
• Lead design workshops, proofs of concept, architecture walkthroughs with client teams.
• Codify learnings to scale delivery across engagements.

Conocimientos

Cloud-native systems

AI deployment & production

AI platforms (OpenAI, Claude, Vertex)

CI/CD & IaC

Business value articulation

Executive stakeholder communication

Non-linear profiles welcomed

End-to-end delivery ownership

Herramientas

Terraform

Helm

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.Youown outcomes: time-to-value, adoption, reliability, and scalability. Not delivery milestones. Outcomes.

The market is beginning to understand what leading technology companies havedemonstrated: 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 scalesisbridged 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

• Embed directly with client engineering and business teams to deploy, scale, and operationalize AI platforms — Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir — inside enterprise environments

• Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, and scalability, with business metrics attached — not just delivery milestones

• Move from ambiguous business problem to working production system through rapid experimentation: days to prototype, weeks to production-ready

• Design and govern AI architectures across the full enterprise stack: identity, data, security, governance, platform layer, and workflow integration

• Translate technical architecture into business impact for client CTO, CFO, and CISO; shape use case roadmaps, ROI backlogs, and AI adoption strategy

• Build reusable patterns, playbooks, and accelerators that the client owns after you leave — enabling the client team to run it without you

• Lead design workshops, proofs of concept, architecture walkthroughs, and code-with sessions with client engineering and leadership teams

• Codify patterns and delivery learnings that scale across engagements and contribute to the growth of the FDE practice

Basic Qualifications

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

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

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

• Strong experience deploying toproduction ,CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.

• 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