Automation & AI Lead UiPath + Azure AI

Key Responsibilities

Strategy & Leadership

• Define and own the enterprise automation and AI strategy, balancing UiPath for RPA and Azure-native AI for intelligent solutions.
• Lead end-to-end delivery — discovery, architecture, build, evaluation, deployment, and hyper care.
• Establish CoE governance: intake, prioritization, reusable accelerators, LLMOps, and ROI tracking.
• Build, mentor, and scale a high-performing automation/AI team across geographies.

Automation Delivery

• Architect and deliver enterprise RPA solutions using UiPath, Power platform.
• Design attended, unattended, and hybrid bots with robust exception handling, reusable frameworks, and audit controls.
• Manage Orchestrator infrastructure (queues, assets, credentials, tenants) and CI/CD for bots.
• Drive adoption of Automations.

AI / LLM Solutioning (Strong Knowledge Required)

• Design and deliver GenAI/LLM-based solutions for document extraction, classification, summarization, decisioning, and conversational interfaces.

• Apply prompt engineering best practices, evaluate model performance, and handle edge cases (e.g., structured data extraction, address matching, exception handling).
• Build RAG (Retrieval-Augmented Generation) pipelines using vector databases (Azure AI Search, Pinecone, etc.).
• Integrate AI agents into RPA workflows to enable agentic automation and human-in-the-loop scenarios.
• Stay current with the evolving GenAI landscape — Azure OpenAI, Anthropic, open-source LLMs, MCP, and agent frameworks.

Azure & Cloud Engineering

• Architect cloud-native automation solutions leveraging Azure services: App Services, Functions, Logic Apps, Service Bus, Key Vault, Storage, API Management, and Azure DevOps.
• Deploy and manage Azure OpenAI workloads (GPT-4o, GPT-5 series, embeddings) with secure prompt engineering, RAG patterns, and content safety.
• Implement CI/CD pipelines for bots and AI components using Azure DevOps / GitHub Actions.
• Ensure cloud cost optimization, governance, and adherence to enterprise security standards.

SAP & Enterprise Integration (Mandatory)

• Lead automation and AI integrations with SAP S/4HANA (SD, MM, FI/CO, PP, WM/EWM) via BAPI/RFC, OData, IDoc, CPI, and Fiori.
• Integrate with Salesforce, Snowflake, ServiceNow, SharePoint, and third-party platforms.
• Architect solutions like intelligent order processing, master data automation, document understanding, and conversational copilots.

Governance & Communication

• Ensure audit-ready traceability — BRD → SDD → evaluation evidence → deployment artifacts.
• Partner with auditors on SOX/ITGC controls, AI risk assessments, and management attestations.
• Act as the single point of contact between IT, business teams, and SI/vendor partners across EMEA, APAC, and Americas.
• Communicate clearly through business-friendly emails, Teams updates, and executive readouts.

Required Qualifications – Automation & AI Lead

✅ Experience

• 10+ years in IT, with 5+ years leading automation/AI initiatives at enterprise scale.
• Proven end-to-end delivery ownership - discovery through hypercare for multiple enterprise programs.
• Experience establishing/scaling an Automation or AI CoE (intake, governance, accelerators, ROI tracking).
• Track record of building and mentoring cross-geography teams.
• Mandatory hands-on UiPath delivery — at least one enterprise-scale program with Orchestrator administration and Document Understanding / AI Center.
• Mandatory hands-on Azure AI delivery — production GenAI/LLM solutions using Azure OpenAI, AI Foundry, AI Search, and Document Intelligence.
• Mandatory SAP integration experience, including at least one S/4HANA program.
• Experience in audit/compliance-driven environments (SOX, ITGC, or equivalent).

️ Technical Skills

• UiPath: Studio, Orchestrator, REFramework, Document Understanding, AI Center, Action Center.
• Power Platform: Power Automate (cloud + desktop), Power Apps, Copilot Studio.
• Strong in attended, unattended, and hybrid bot design, exception handling, and CI/CD for bots.
• Solid grounding in GenAI fundamentals: embeddings, tokenization, fine-tuning vs RAG, evaluation.
• Advanced prompt engineering: structured outputs, function/tool calling, guardrails, edge-case handling.
• Hands-on RAG pipelines with vector stores (Azure AI Search, Pinecone) — chunking, hybrid search, re-ranking.
• Experience with agentic frameworks: Semantic Kernel, LangChain, AutoGen, Azure AI Agent Service, MCP.
• Azure AI: Azure OpenAI (GPT-4o, GPT-5, embeddings), AI Foundry, AI Search, Document Intelligence, Content Safety.
• DevOps & LLMOps: Azure DevOps, GitHub Actions, CI/CD, prompt versioning, observability, cost optimization.

Soft Skills

• Exceptional communication — translates AI/automation concepts for executive and business audiences.
• Strong stakeholder management across IT, business, and SI/vendor partners (EMEA, APAC, Americas).
• Highly detail-oriented and analytical, with a bias for traceability and governance.
• Comfortable navigating ambiguity and driving adoption of industry best practices.