Rovo & AI Prompt Engineer

Strategic Technology Effectiveness, part of Accenture’s Technology Strategy & Transformation Organization. We rebuild how large enterprises define, design and govern software, and we design and implement the agentic software and processes that run it. That work changes the operating model an engineering organization runs on, the ways of working underneath it, and the tooling that makes both of those real.

We start with evidence. Cycle time, flow efficiency, WIP and throughput show where delivery stalls, and that diagnosis sets the target. What we design from it is AI-native by construction. We redesign intake and prioritization, so demand meets real capacity, and rebuild the path from request to release so planning, build, review, testing and deployment connect to each other instead of handing off through spreadsheets and status meetings.

Most of our build work sits upstream, where the cost of rework gets set: requirements generation, user story synthesis, design review, architecture validation. That means creator and reviewer agent patterns, tool-use orchestration, and multi-agent workflows on enterprise frameworks, with a working understanding of what each pattern costs in tokens and where it breaks. We treat the lifecycle as a system and a product itself - built to operate at a speed required for the AI era.

Then we make it stick. Engineering teams move to AI-augmented work and stay there, which is what separates a delivery organization where AI is how software gets made from the working pilot. Practitioner depth in delivery operating models and AI, paired with Accenture’s global platform and technology expertise, puts us in front of delivery organizations at a scale few firms reach.

The Work

Design, optimize, and govern enterprise AI experiences using Atlassian Rovo and LLMs. This role combines prompt engineering, knowledge orchestration, AI agent development, and workflow automation to deliver secure, accurate, and scalable AI capabilities that improve productivity and decision-making.

Role-Specific Responsibilities:

• Design enterprise AI prompts and conversational experiences.
• Develop and maintain Atlassian Rovo Agents.
• Build AI-powered knowledge assistants and workflow automations.
• Curate enterprise knowledge to improve AI-generated responses.
• Establish prompt libraries, standards, and governance processes.
• Evaluate and optimize AI performance using quantitative and qualitative metrics.
• Collaborate with product owners, solution architects, AI engineers, and business stakeholders.
• Promote AI adoption and prompt engineering best practices across the organization

Artificial Intelligence (AI), Machine Tool, Technical Strategy, Software Design, Testing, Establish Priorities, Spreadsheets, Artificial Intelligence (AI), Construction Design, Automation