AI Transformation Lead, Agentic Workflows & LLM Systems
Overview
You will own the end-to-end delivery of AI-driven workflows that turn frontier capabilities like Celeste and Claude into production systems used by GTM and Finance teams. You'll scope business problems, design agents and integrations, ship them into live systems like OP4i, and prove impact with real usage data. Working within a defined governance model, you'll embed directly with Sales, Services, and Success teams to identify friction and translate ambiguous requests into production-ready solutions. This hands-on role also codifies successful patterns into reusable playbooks that cut concept-to-production cycle time. You'll sit on the AI Advisory Council and partner with Applied AI, IT, and Operations to shape the enterprise AI roadmap.
What You'll Do9
- 1Lead end-to-end delivery of AI workflows, from intake and prioritization through build, UAT, and production rollout, hitting broad adoption within 90 days.
- 2Embed directly with Sales, Services, Success, and Support teams to scope real workflow friction and define success metrics tied to time savings and data quality.
- 3Design and build integrations across OP4i, M365, Celeste, and Claude, including new Celeste Playbooks and Claude Skills.
- 4Balance scope, speed, and quality trade-offs to protect delivery timelines and outcomes in ambiguous environments.
- 5Translate ambiguous business requests into scoped, governed, production-ready solutions with a clear owner and measurable impact.
- 6Codify successful patterns into reusable playbooks, templates, and frameworks that scale beyond a single deployment.
- 7Provide structured feedback on real-world usage and performance data to IT and the AI Advisory Council.
- 8Identify and flag data governance risks, including access control gaps and write-back conflicts, before they become production issues.
- 9Develop an operating model to scale Playbooks and agents across Business Transformation Managers and Operations teams.
Requirements6
- 15+ years deploying AI/ML systems into production, including LLM-based applications, with strong understanding of model behavior on business workflows.
- 2Experience working directly with senior stakeholders, translating technical concepts into business value and driving adoption.
- 3Demonstrated ability to scope and deliver complex systems in fast-moving, ambiguous environments with strong judgment on risk and prioritization.
- 4A blend of engineering, consulting, and product thinking, with strong systems and architectural judgment and an ownership mentality.
- 5Excellent communication across technical and non-technical audiences, simplifying complexity and driving alignment.
- 6Comfort operating inside a structured governance model, balancing speed with enterprise-scale discipline.
Salary Insight
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