• Serve as a trusted advisor to healthcare executives on AI, automation, agentic transformation, and enterprise technology strategy. • Lead strategic discussions with CIOs, CTOs, Chief AI Officers, Enterprise Architects, and other senior stakeholders. • Help healthcare organizations define long-term AI and automation roadmaps aligned to business, operational, and patient outcomes. • Evaluate how UiPath, hyperscaler AI services, healthcare-specific AI vendors, workflow platforms, agentic technologies, and point solutions fit within an organization’s technology ecosystem. • Develop future-state transformation strategies and architecture recommendations that support scalable enterprise adoption. • Advise customers on AI governance, operating models, platform strategy, and organizational readiness. • Articulate the differentiated value of Agentic Automation and help customers identify where UiPath can drive the greatest impact. • Translate emerging developments in AI, automation, and agentic technologies into practical healthcare transformation opportunities. • Guide executive stakeholders on implementation approaches, change management considerations, and value realization strategies. • Partner with internal Product, Go-To-Market, Technology Alliances, and Industry teams to ensure that our solutions are comprehensive and match the needs of our customers. • Represent UiPath as a healthcare thought leader through executive briefings, industry conferences, customer events, and market-facing engagements. • Share industry trends, best practices, and competitive insights across the UiPath organization.

• The Senior Agentic AI Engineer is a hands-on builder responsible for designing, developing, and deploying AI-powered autonomous workflows and agentic systems. • Design and build LLM-powered agentic workflows using Azure AI Foundry and Anthropic Claude APIs. • Develop multi-step AI agent pipelines using orchestration frameworks integrated with enterprise systems. • Implement Model Context Protocol (MCP) integrations to enable AI agents. • Apply security-by-design principles throughout all AI agent development. • Build, test, and iterate on prompts, system instructions, and agent reasoning chains. • Partner with the Backend Integration Engineer to connect agent workflows to existing enterprise API infrastructure. • Collaborate with the AI Business Analyst to translate business use cases into technical agent requirements. • Participate in code reviews and maintain internal documentation.

• Own a set of interconnected product areas and be accountable for their strategy, roadmap, and outcomes. • Own the Messaging Platform — the application where live agents handle concurrent conversations, access customer context and knowledge, and collaborate with AI. • Define and execute the Virtual Agent and channels roadmap. • Lead the AI Services that power the surface — such as automatic conversation summary, voice-to-text transcription and AI-augmented response generation. • Be the go-to expert on Human + AI collaboration. • Own the external documentation for this surface as part of the product. • Set strategy and own the roadmap — balancing active customer commitments, tech debt, and platform bets. • Work directly with customers and account teams to prioritize and sequence delivery. • Establish metrics and telemetry for each product area so outcomes are measurable and decisions are data-driven.

• Lead the technical engagement with a focused set of ISV partners, working closely with their Software Platform Architects. • Together you'll set the objectives, timelines, and adoption plan for each account. • Stay hands-on: design and ship the code, methods, and reference architectures that bring RAG, inference, and multi-agent, long-horizon workflows to life on our stack (NeMo, Nemotron, NeMo Agent Toolkit, NIM, Dynamo, TensorRT-LLM) and open tools (vLLM, LangChain, vector DBs, MCP, A2A). • Lead the technical strategy and execution: run the cadence, track adoption, and share what you learn with our Product, Engineering, Research, and Solution Architecture teams to land the best solution. • Build breadth across the agentic AI lifecycle, with depth in a few areas that fit you: fine-tuning (PEFT, SFT), post-training and RL from verifiable rewards, reasoning, advanced RAG, multi-agent workflows, skills/harness engineering, agent evaluation and observability, and production inference. • Be the voice of the partner inside NVIDIA. Bring their needs and architecture to our Product, Engineering, and Research teams, and help shape the roadmap with what you see across industries. • Grow deep expertise in agentic platform architecture, and keep up with our fast-moving field and stack so you can give partners the best guidance.