AI Experience Strategist_Q227

Infosys; Maharashtra; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Infosys in Maharashtra seeks a senior CX/AI experience leader to define CX vision, north-star, experience principles, and strategic roadmaps for AI-enabled products and services. You will map journeys, design future-state experiences, and establish governance to scale responsible AI adoption.

Build data-backed business cases, define success metrics across CX and operational impact, and translate AI capabilities into tangible user outcomes.

Qualifications

Responsibilities

• 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.
• 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.
• 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 elevate 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.

Job description

• 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.

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.

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 elevate 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.

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.