Job Summary
We are seeking an experienced Automation & AI Lead to drive enterprise intelligent automation and AI strategy. The ideal candidate is a hands-on leader with strong UiPath expertise for RPA delivery and deep Azure-native AI architecture skills for all AI/GenAI solutioning. This role combines technical depth, architectural vision, and excellent communication — with a focus on building production-grade AI solutions on Azure and orchestrating them through UiPath where appropriate.
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.
Skill Requirements
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.
Other Requirements
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.