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Infosys

AI Experience Strategist_Q227

Pune, India

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hirly's read of this role

Seniority
Mid level
Country
IN
Work mode
On-site / unstated
First seen by hirly
27 Sept 2026

Derived automatically from the posting.

the posting

Responsibilities

1. Experience Strategy & Transformation

Define CX vision, north-star, experience principles, and strategic roadmaps for AI-enabled products and services.

Identify high-impact opportunities across journeys, operations, and AI-led transformation.

Lead journey mapping, service design, and future-state experience definition to unlock value.

Establish experience governance frameworks that support responsible, scalable, and measurable AI adoption.

2. Business Value & Impact

Build data-backed business cases with clear ROI, adoption, trust, efficiency, and value-realization measures.

Define success metrics across CX, task completion, containment, fallback performance, adoption, revenue impact, and operational efficiency.

Align AI experience strategy with business, product, technology, risk, and financial goals.

Translate AI capabilities into practical user outcomes, prioritised use cases, and transformation roadmaps.

3. AI-led Innovation

Identify and frame AI-driven experience opportunities across Generative AI, conversational AI, copilots, automation, and agentic workflows.

Conduct AI capability mapping to determine where AI can assist, augment, automate, or escalate user tasks.

Create advanced personas, mental models, behavioral models, and AI interaction scenarios.

Design dynamic information architecture, dialogue flows, multi-turn interaction models, and generative interface patterns.

Develop prompting frameworks, prompt libraries, and reusable GenAI interaction patterns.

Define containment strategies, fallback mechanisms, escalation pathways, and human handoff experiences.

Design agentic function schemas and collaborate with engineering teams on function-calling workflows for AI assistants and autonomous agents.

Conduct simulations, hallucination audits, AI behavior assessments, and usability testing for AI-generated outputs.

Define LLM evaluation datasets, benchmarks, and quality criteria to assess accuracy, relevance, safety, and user trust.

Partner with data and engineering teams to shape AI-enabled solutions that are usable, accessible, responsible, and business-aligned.

4. Business Development & Thought Leadership

Contribute to proposals, strategic pitches, AI innovation workshops, and client discovery engagements.

Represent design in client discussions and industry forums with a strong point of view on human-centered AI.

Education

Bachelor of Design,Bachelor of Engineering

Original posting on Infosys's site ↗

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