Deployment Practitioner

Project Role : Deployment Practitioner

Project Role Description : Assist the Deployment Lead in all deployment-related tasks including work planning, scheduling, budgeting, metrics, training, pilots and resources.

Must have skills : Generative AI

Good to have skills : NA

Minimum 15 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary:

We are looking for a senior technology and transformation leader with 16–25 years of experience to shape and lead enterprise GenAI/Agentic AI programs from opportunity identification and business case through solutioning, delivery, adoption and value realization. The role will partner with executive stakeholders to define AI strategy, prioritize high-value use cases, lead large multidisciplinary teams, manage program outcomes and scale successful solutions across the enterprise.

Roles & Responsibilities:

• Identify and prioritize GenAI/Agentic AI opportunities through business process and value-stream analysis, evaluating business value, feasibility, investment, risk and expected ROI.
• Shape AI and technology strategies, business cases, transformation roadmaps and solution approaches aligned to enterprise and business objectives.
• Lead end-to-end delivery of complex AI transformation programs across solutioning, architecture, application development, system integration, testing, deployment, adoption and production operations.
• Own program governance, financials, resources, risks, dependencies, delivery outcomes and executive stakeholder communication across multiple workstreams.
• Drive adoption, benefits realization, reuse and scale of successful AI solutions across business functions, geographies and programs.
  
  
  

• Strong understanding of enterprise application development, system integration, APIs, microservices, cloud architecture, SDLC, modernization and enterprise technology landscapes.
• Strong understanding of GenAI/LLM and Agentic AI, including AI agents, single/multi-agent architectures, orchestration, prompt engineering, tool/function calling, RAG, embeddings, vector databases and knowledge retrieval.
• Ability to evaluate GenAI, Agentic AI, automation, traditional software or hybrid approaches and guide solution architecture and technology selection.
• Strong understanding of Responsible AI, AI security, privacy, guardrails, evaluation, enterprise governance, scalability, performance and operational readiness.
  
  
  

• Experience with enterprise AI platforms such as Amazon Bedrock, OpenAI, Anthropic or Azure OpenAI and frameworks such as LangChain, LangGraph, AutoGen, CrewAI or equivalent is preferred.
• Strong experience in program financial management, commercial models, proposals/RFPs/RFIs, account growth, executive presentations and client advisory is desirable.
• Proven ability to lead large multidisciplinary teams, mentor Managers/Technical Leads/Architects, establish reusable AI capabilities and drive measurable outcomes such as productivity, cost savings, cycle-time reduction, quality improvement and revenue impact.