AI LLM Technology Architecture Sr Mgr (Bengaluru)

AI LLM Technology Architecture Sr Mgr (Bengaluru)

13 Oct
|
Accenture
|
Bengaluru

13 Oct

Accenture

Bengaluru

Skill required: Tech for Operations - Artificial Intelligence (AI)
Designation: Senior AI Native Product Manager
Qualifications:Any Graduation
Years of Experience:13 to 16 years

Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Songall powered by the worlds 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.
What would you do Reinvention Deployment Engineer (RDE) is an approach used by Accenture to reimagine and accelerate the delivery of engineering and RD 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 a Senior AI Native Product Manager for the RDE POD, you lead the definition, build, and scale of GenAI and agentic AI products embedded within live enterprise environments. You operate as the senior product owner across one or more outcome pods, converting ambiguous client problems into focused, production-grade product bets that deliver measurable business value. You combine strong product judgment with hands on technical depth, guiding architecture and engineering decisions while owning adoption, quality, and commercial outcomes. You are also AI native in how you work, using AI tooling extensively to accelerate discovery, synthesis, prototyping, and decision-making, and you raise the product bar for the pods and engineers you lead.
What are we looking for Product Technical10+ years in product management, including ownership of enterprise software products or platforms from concept through launch and scale. 3+ years hands on building, launching,



or managing AI native products leveraging LLMs, agents, retrieval systems, and workflow automation. Robust software engineering literacy (Python,SQL); able to reason about system design, APIs, data pipelines, and cloud native architecture.Consulting Human SkillsProven ability to operate in client facing, high ambiguity environments and influence senior stakeholders. Strong ownership mindset
Roles and Responsibilities: 1. Product Direction Client DiscoverySet product vision for your area defining who the product is for, why it will win, and what the team should deliberately not build. Embed with client business, technology, and operations leaders to discover high impact, repeatable problems worth solving with GenAI and agentic AI. Make clear tradeoffs across customer value, technical feasibility, commercial potential, speed, quality, and strategic fit.2. AI Native Agentic Product EngineeringShape agentic products defining agent behavior, tool use, orchestration, memory, uncertainty handling, and human in the loop escalation. Guide solution architecture for LLM powered applications, including prompt workflow orchestration, tool calling agents, and RAG patterns. Stay hands on enough to make credible technical calls and unblock engineering in mission-critical environments.3. Zero to One Delivery End to End OwnershipLead the full lifecycle from customer problem, prototype, design partner validation, production, scaled adoption. Write clear product briefs, requirements, decision documents, and acceptance criteria without creating unnecessary process. Own outcomes after launch adoption, usage, retention, customer value, and product quality, not just roadmap delivery.4. Commercial Validation Pod LeadershipValidate demand and commercial value with design partners across desirability, usability, technical performance, business value, and willingness to pay. Act as technical and product authority within the RDE pod, guiding architecture, coding standards, and engagement quality. Mentor CL7 CL8 product and engineering talent on AI patterns, product judgment, and AI-native ways of working.

Qualification
Any Graduation

📌 AI LLM Technology Architecture Sr Mgr (Bengaluru)
🏢 Accenture
📍 Bengaluru

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