Forward Deployed AI Engineer - Senior Manager

A production engineering role embedded inside a client's enterprise, working shoulder to shoulder with their teams to make complex AI platforms work in real organizational environments. Accenture says this is not a consulting, project delivery, or research role: Forward Deployed AI Engineers own outcomes such as time-to-value, adoption, reliability, and scalability, and form the execution spine of its Reinvention Deployment Engineering pods.

Responsibilities

• Own account-level AI transformation, from platform selection and architecture through enterprise-wide adoption.
• Hold accountability for deployment outcomes (time-to-value, reliability, adoption, ROI), reported to client executive leadership.
• Translate executive strategic intent into production AI systems across the enterprise.
• Define enterprise AI architecture standards and governance spanning identity, data, security, multi-platform integration, and AI lifecycle management.
• Work with client CTO, CFO, and CISO on AI investment strategy and multi-year roadmaps.
• Codify reusable patterns and playbooks for the global FDE practice; lead executive workshops and architecture reviews.

Qualifications

• Bachelor's degree or college diploma in a related field.
• 10–15 years of engineering experience with cloud-native systems (APIs, microservices, containers, serverless).
• At least 1 year designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production.
• At least 7 years working with AI platforms such as OpenAI, Claude, Vertex AI, or open-source models; experience building multi-provider AI abstraction layers.
• 10–15 years leading software engineering teams, with end-to-end delivery ownership in client-embedded environments.