Skill required: Tech for Operations - Artificial Intelligence (AI)

Designation: AI LLM Technology Architecture Manager

Qualifications:Any Graduation

Years of Experience:9 to 13 years

About Accenture

Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song— all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 784,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com

What would you do

Reinvention Deployment Engineer (RDE) - is an approach used by Accenture to reimagine and accelerate the delivery of engineering and R&D solutions. It focuses on combining human expertise with AI-driven agents to enhance innovation velocity, streamline processes, and reduce time to market for products and services. RDE emphasizes a value-driven mindset, where humans define objectives and ethical guardrails while AI
agents handle scale, speed, and data-driven execution. As an AI Native Product Manager within the RDE POD, you are responsible for translating client needs and business opportunities into AI-powered products and capabilities. You work closely with clients, engineers, architects, designers, and business stakeholders to define, build, and scale GenAI and Agentic AI solutions that solve real-world enterprise challenges.
You combine strong product management skills with practical understanding of AI technologies, helping teams deliver high-quality products that create measurable business value. You leverage AI tools extensively for research, synthesis, prototyping, and decision-making, while contributing to an AI-native product culture within the pod. What are we looking for
Adoption & Value Realization
Track product success metrics including usage, customer satisfaction, adoption, and business impact.Support rollout strategies and change management activities to maximize product utilization. Identify opportunities for enhancements, scalability, and reusable product patterns.Ensure delivered solutions continue to meet customer and business objectives after launch.
Consulting & Human Skills
Strong stakeholder management and communication skills in client-facing environments.Ability to work effectively in ambiguous and fast-paced environments. Roles and Responsibilities:
1. Product Discovery & Customer Understanding
Partner with client stakeholders to understand business challenges, operational pain points, and user needs.
Assist in shaping product vision, roadmap, and priorities for assigned product areas.
Conduct discovery activities, gather customer feedback, and identify opportunities for GenAI and agentic solutions.
Translate business requirements into clear product objectives and actionable requirements.
2. AI-Native Product Development
Define product capabilities leveraging LLMs, agents, retrieval systems, workflow automation, and AI orchestration patterns.
Collaborate closely with engineering teams to design effective AI-enabled user experiences and workflows.
Contribute to decisions related to prompts, RAG implementations, agent behaviors, tool integration, and evaluation approaches.
Stay current with emerging AI technologies and recommend improvements to existing products.
3. Delivery & Product Execution
Drive product initiatives from concept through development, testing, release, and adoption.
Create and maintain product requirements, user stories, acceptance criteria, and prioritization artifacts.
Work with agile teams to ensure timely delivery and alignment with client goals.
Monitor product performance and support continuous improvement based on user feedback and business outcomes.
4. Stakeholder & Pod Collaboration
Partner with business, technology, and operations teams to align product priorities and execution plans.
Support design partner engagements by collecting feedback and validating product effectiveness.
Facilitate communication between engineering teams and stakeholders to resolve ambiguities and delivery challenges.
Contribute to knowledge sharing and adoption of AI-native product management practices across the pod.