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Key Responsibilities
1. Leadership – Office of Automation & AI
• Establish and lead the Office of Automation & AI, driving vision, governance, and execution.
• Define strategic priorities for AI, automation, and agentic transformation across IT operations and delivery.
• Act as the single point of accountability for AI initiatives across IT Operations and SDLC
2. Enterprise AI & Agentic Transformation
• Serve as the central point of contact for all AI-driven transformation initiatives across:
◦ IT Service Management (ITSM)
◦ Software Development Lifecycle (SDLC)
◦ Infrastructure and Application Support
• Drive adoption of agentic AI solutions to enhance efficiency, reliability, and scalability of IT services.
• Champion a culture of innovation and continuous improvement using AI-led interventions.
3. Solution Architecture & Use Case Realization
• Act as the Lead Solution Architect for AI and automation initiatives.
• Collaborate with:
◦ Central AI Engineering teams
◦ IT Service Delivery leaders
◦ Tech Stack owners – Azure AI, AWS, Nvidia, Anthropic & SaaS providers such as SalesForce, SAP,
• Identify, define, and prioritize high-value use cases across ITSM and SDLC.
• Evaluate and leverage:
◦ Enterprise AI agent catalogs
◦ Third-party AI/automation solutions
• Guide solution design ensuring alignment to business outcomes and technical feasibility.
4. AI Ecosystem & Stakeholder Collaboration
• Partner with central AI engineering teams to:
◦ Align on reusable AI capabilities and platforms
◦ Prioritize initiatives based on business impact and ROI
• Work closely with client stakeholders to tailor solutions for their environments.
• Ensure seamless integration of AI solutions into existing IT systems and processes.
5. Roadmap, Governance & Adoption
• Define and deliver the Agentic Technology Roadmap across ITSM and SDLC.
• Present roadmap to executive stakeholders and secure technical and business approvals.
• Establish governance frameworks to ensure:
◦ Responsible AI adoption
◦ Risk mitigation and compliance
◦ Performance tracking and value realization
• Drive implementation, adoption, and scaling of AI solutions across client environment.
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Job ID: 148484413
Skills:
SAP BTP, SAP Analytics, GenAI, Agentic AI, Datasphere, ML models, cloud AI services
Skills:
data engineering , Ml, Apis, Deep Learning, Nlp, MLops, Python, LangChain, Generative AI, AWS Bedrock, LLMs, RAG frameworks, LLMOps, Hugging Face, cloud platforms, Ai, vector databases, Azure OpenAI, Google Vertex AI, OpenAI, LlamaIndex
Skills:
Apis, Scalability, Performance, non-functional requirements, explainability, Communication Protocols, data platforms, agent orchestration frameworks, modeling approaches, hybrid reasoning, integration of AI with enterprise systems, AI architecture, Ethics, Govern model lifecycle, role-based agents, Security, microservices architecture, AI frameworks, compliance with AI policies
Skills:
Ml, Tensorflow, Pytorch, Docker, Azure, Kubernetes, Python, generative AI, cloud platforms, Ai, RAG methodologies, MLOps tools
Skills:
snowflake , Logging, Kafka, Docker, Flask, Python, AWS, Graphql, REST, Gcp, Databricks, FastAPI, Azure, Kubernetes, Pinecone, CI CD, LangChain, LLMs, Vector DBs, Monitoring, agent frameworks, prompt engineering, FAISS, Lakehouse, evaluation pipelines, RAG, experiment tracking tools, Weaviate, LlamaIndex
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