Forward Deployed Product Manager (FDPM)

Accenture•Columbus, OH

11d•$54,400 - $196,000•Hybrid

About The Position

The Advanced Technology Centers (ATCs) is the engine for reinvention in our clients’ transformation journey. Powered by more than 255,000 people across 24 countries, ATCs will provide our clients with seamless access to industry insights and innovative technology solutions. The Advanced Technology Centers (ATCs) make tremendous impact in solving our clients’ business problems leveraging Innovation, Intelligence, Industry insights, new IT and new technology skills. Now, with the global environment changing at a faster pace, our clients are facing unprecedented challenges, and they need us more than ever before. As a Network, ATCs are positioned to unlock greater opportunities and exponential value for our clients. For our clients, the Network provides the strength of our geographic diversity, greater resilience, and seamless access to the deepest industry knowledge, the latest in Gen AI solutions, and tech expertise from around the world. For our people, it brings an opportunity to shape truly boundaryless career paths in a highly collaborative team of experts where they can learn from each other and solve the world’s most complex client challenges. You are an AI-native Forward Deployed Product Manager who leads a single AI delivery team built on an agentic harness (the orchestration environment of agents, skills, specs, and context that produces and runs the product). You turn business problems into the specs the harness executes, run the loop yourself, and demonstrate the working product and its value directly to clients. You build and skill your own agents, engineer the context the harness reasons over, and prototype to shape a product fast. You are technically fluent and hands-on, without replacing the engineering accountability for production code and operations.

Requirements

Building agents: hands-on experience creating and skilling AI agents (skills, tools, and context / markdown files).
Spec-driven development: writing specifications and driving development from them.
Context engineering: curating the knowledge, retrieval, and memory an AI system reasons over.
Vibe coding and prototyping: building clickable prototypes and concepts with AI tools.
Generative AI and LLM fundamentals: working knowledge of retrieval-augmented generation, embeddings, prompt engineering, AI agents, and agentic workflows.
Product or delivery leadership: experience leading product management, technical product management, delivery management, or business analysis in complex environments.
Technical fluency: APIs, integrations, cloud platforms, and modern architectures; able to discuss interaction and dependency points with engineers (without owning the implementation).
Client-facing delivery: ability to run client demos and communicate product value independently.
Leadership through influence: ability to lead without authority, make decisions under ambiguity, and operate effectively in evolving client environments.
A minimum of three years of experience of product, technical-product or delivery leadership experience with technical fluency (APIs, integrations, cloud) and strong client-facing delivery.
A minimum of one year of experience with AI-first skills (building agents, spec-driven development, context engineering and prototyping with AI).
A minimum of one year of experience with GenAI and LLM fundamentals
Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate Degree, must have minimum 6 years work experience.)

Nice To Haves

Hands-on expertise with enterprise AI tools such as GitHub Copilot, Claude Code, or OpenAI Codex; relevant certifications a plus.
Experience in regulated industries or environments with significant privacy, security, compliance, or risk requirements.
Product management, Agile, Scrum, SAFe, or related professional certification.

Responsibilities

Lead discovery and mobilization (first ~2 weeks): assess what the team and client need, break down the problem, and stand up the agentic harness for the product.
Build and skill AI agents for the harness: create agent skills and tools, author markdown / context files, and engineer the context the harness reasons over.
Write specifications and drive spec-driven development: author clear, open specs the AI harness can pick up and iterate on.
Prototype and vibe-code to shape the product: build clickable prototypes and concepts with AI to align stakeholders quickly (concepts and UI, not production code).
Partner with stakeholders on requirements: gather and continuously refine evolving business requirements into the technical form the harness executes and iterates.
Run the harness and run demos independently: show the working product, the value delivered, and how the harness operates at each step, without needing an engineer on the call.
Shape and prioritize the feature pipeline: features within a sprint, epics across sprints, keeping the delivery runway healthy.
Manage the team to stakeholder expectations: own delivery commitments and keep the team aligned to what stakeholders expect.