• Lead conversational design for agentic experiences, defining interaction patterns, dialogue structures, and content strategies that enable users to complete complex tasks with ease, clarity, and confidence • Design end-to-end conversational flows across prompts, responses, follow-up actions, clarifications, error handling, and recovery paths • Create experiences that balance utility, transparency, trust, and delight, helping users understand agent capabilities, system limitations, and next-best actions • Partner closely with product managers, designers, engineers, researchers, and AI/ML teams to shape product direction and ensure conversational experiences are feasible, valuable, and high quality • Translate ambiguous problem spaces and emerging AI capabilities into clear conversational frameworks, principles, and reusable patterns • Develop and maintain standards for personality, tone, voice, interaction behavior, and conversation quality across agentic experiences • Use customer insights, usage signals, evaluation frameworks, and testing outcomes to refine conversational experiences and improve task success, comprehension, and satisfaction • Advocate for human-centered, inclusive, and responsible design approaches in AI-powered interactions • Contribute to scalable design systems, guidance, and best practices for conversational and agentic UX across teams • Help Autodesk evolve how conversational interfaces support real workflows, reduce friction, and create more seamless Design and Make experiences • Collaborate with content strategists across AEC's product teams to ensure product-specific considerations are accounted for and drive connectivity with conversation designers across Autodesk for unified approaches and best practices

• Engage the HCLS AI Startup Community in the UK, France, and the Nordics • Build and scale programs that connect regional HCLS startups to NVIDIA technologies • Engage regional Venture Capital firms and funding entities • Drive Regional Strategy, Execution, and Operational Excellence • Act as Regional Interface and SME

• Own the People Analytics roadmap and delivery, expanding beyond foundational reporting to introduce predictive, automated, and strategic insights • Serve as the primary liaison between People and IT’s analytics team, with dotted-line management of IT’s full-time People Analytics resource — ensuring alignment, prioritization, and timely execution of work; Deliver actionable insights through dashboards and analytics that accelerate data fluency and support leadership decisions on hiring, retention, engagement, and organizational effectiveness. • Lead execution of the People AI strategy — defining what “AI for People” means for Welbe and identifying opportunities that drive measurable impact • Manage discovery and implementation of AI tools and frameworks to support talent, team member experience, and organizational decision-making • Guide ethical and responsible AI integration across People initiatives, establishing principles around fairness, transparency, and data security; Translate strategic AI priorities from leadership conversations (CPO & CEO) into practical, scalable solutions and pilots within the People organization • Champion a digital-first mindset across the People team, embedding technology, analytics, and experimentation into everyday decision-making; Proactively identifying opportunities for digitization and automation within HR processes to enhance scalability and personalization • Influence senior leaders on how data and AI can evolve our people team strategies, champion of supervisor adoption of AI and technology for people related tasks; Mentor and build analytics literacy across the People function, enabling teams to think differently about insights and action

About the Role: At Fetch, we’re building AI and automation systems that make our work smarter, faster, and more scalable. The AI Operations team ensures our models and workflows perform with quality, reliability, and measurable impact. As a Senior Automation Specialist, you’ll own evaluation and dataset workstreams that improve AI system performance. You’ll define what “good” looks like, design how we measure it, and build the datasets, evaluations, and automations that turn insights into action. This role is ideal for someone who is self-directed, biases toward action and rapid iteration, and takes initiative to turn ambiguous problems into structured, scalable solutions. This is a full-time role that can be held from one of our US offices or remotely in the United States. Role Responsibilities: - Own evaluation & datasets: Define evaluation approaches, design gold datasets (GDS), and ensure coverage of real-world scenarios and edge cases - Build evaluation systems: Develop manual and automated evals, including LLM-as-judge patterns, to measure model quality and performance - Translate ambiguity into structure: Turn open-ended questions into clear evaluation frameworks and execution plans - Build automations: Create automations that improve workflows, including dataset creation, evaluation pipelines, and lightweight operational processes - Measure and iterate: Define and track performance metrics; refine datasets, evaluations, and workflows based on results - Drive execution forward: Operate with urgency and ownership; identify next steps, unblock progress, and move work forward with minimal oversight - Collaborate cross-functionally: Partner with other Automation Specialists, engineering, cross-functional stakeholders, and project leads to ensure high-quality, timely project deliverables - Improve systems: Identify gaps and implement scalable improvements to evaluation and data workflows Minimum Requirements: - 3+ years of experience designing or working with evaluation frameworks, datasets, or quality measurement systems - Experience building or managing datasets (labeling, QA, iteration) - Ability to independently drive tasks from problem definition to execution - Hands-on experience with AI tools, LLM workflows, or automation platforms - Experience in defining and tracking model performance - Basic scripting or data skills (SQL, Python, etc.) Preferred Requirements: - Experience with LLM-as-judge or model evaluation techniques - Familiarity with prompt evaluation or benchmarking approaches - Experience productionizing evaluation workflows with engineering teams Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is [$75,000 - $85,000]. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.