Deployment Practitioner

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:

1. Identify and prioritize GenAI/Agentic AI opportunities through business process and value-stream analysis, evaluating business value, feasibility, investment, risk and expected ROI.

2. Shape AI and technology strategies, business cases, transformation roadmaps and solution approaches aligned to enterprise and business objectives.

3. Lead end-to-end delivery of complex AI transformation programs across solutioning, architecture, application development, system integration, testing, deployment, adoption and production operations.

4. Own program governance, financials, resources, risks, dependencies, delivery outcomes and executive stakeholder communication across multiple workstreams.

5. Drive adoption, benefits realization, reuse and scale of successful AI solutions across business functions, geographies and programs.

Professional & Technical Skills

1. Strong understanding of enterprise application development, system integration, APIs, microservices, cloud architecture, SDLC, modernization and enterprise technology landscapes.

2. 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.

3. Ability to evaluate GenAI, Agentic AI, automation, traditional software or hybrid approaches and guide solution architecture and technology selection.

4. Strong understanding of Responsible AI, AI security, privacy, guardrails, evaluation, enterprise governance, scalability, performance and operational readiness.

Additional Information:

1. 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.

2. Strong experience in program financial management, commercial models, proposals/RFPs/RFIs, account growth, executive presentations and client advisory is desirable.

3. 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.