Job at a glance
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 hackajob is partnering directly with Accenture to hire for this role.
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, 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 Engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
Deepexpertisein designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments. Experience with AI platforms OpenAI, Claude, Vertex AI, plus open-source models including building abstraction layers to manage multi-provider pipelines. 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 ondemonstrateddeployment experience and outcome ownership, not CV pattern matching About Accenture Accenture is a leading global professional services company that helps the worlds leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen servicescreating tangible value at speed and scale.
We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change to