Varicent is seeking an AI Ops & Transformation Lead to lead enterprise-wide adoption of GenAI and automation. This role will identify high-impact use cases, scout and evaluate emerging AI/automation technologies, and manage the delivery of transformational projects that drive measurable efficiency across the business.

You don’t need to be a deep coder, but you must bring strong technical fluency and curiosity — able to translate business needs into structured requirements, experiment with no-code/low-code platforms and work closely with developers to bring automation to life.

Key Responsibilities 

• Workflow Design & Execution
• Partner with cross-functional leaders to identify, scope, and document AI use cases.
• Design, test, and iterate AI-powered workflows and automation agents (using platforms like Relevance, Make, Retool, Zapier, or custom builds).
• Maintain clear documentation of workflows, logic, and dependencies for scale and handover.
• Monitor adoption and performance; troubleshoot and optimize through feedback loops.
• Technology Scouting & Evaluation
• Stay curious about the evolving AI/automation landscape.
• Identify new tools, platforms, or methods that could accelerate efficiency or transformation at Varicent.
• Run pilots and recommend technologies that best fit business needs.
• Program Management
• Maintain and prioritize an AI/automation backlog based on ROI and impact.
• Translate business needs into structured requirements for Dev team.
• Track progress, adoption, and ROI; report outcomes to CE and Ops Council.
• Team Leadership
• Manage 2 Developers dedicated to AI/automation projects.
• Set priorities, allocate tasks, and ensure timely delivery of solutions.
• Encourage experimentation, scrappiness, and a learning mindset.
• Enterprise Enablement
• Act as internal evangelist for AI and automation.
• Educate teams on how workflows support their goals; provide enablement and playbooks.
• Partner with functional “AI champions” across GTM, Finance, Ops, and HR to scale adoption.
• Transformational Projects
• Lead initiatives where AI unlocks step-change efficiency (e.g., GTM automation, reporting, compliance).
• Collaborate with IT, Ops, and Finance on system redesigns leveraging GenAI.

Knowledge, Skills and Experience

• 6–10 years in operations, program management, automation, or enablement.
• Experience with workflow/automation platforms (Make, Zapier, Retool, Relevance) or system integration.
• Familiarity with data tools (SQL, Excel) and APIs; basic coding knowledge (Python/JavaScript) a plus but not required.
• Strong technical curiosity — energized by exploring new AI tools, experimenting, and finding ways to apply them to real business problems.
• Able to translate between business and technical audiences; strong documentation and communication skills.
• Proven ability to manage technical contributors and deliver cross-functional programs.
• Iterative, experimental mindset; comfortable with ambiguity and rapid change.

Performance Based Success Criteria

What are you expected to own, teach, learn and improve once you're on the job? What should you accomplish by when? How your career will progress throughout the year?

1-3 Months

• Stakeholder Engagement: Built strong working relationships with cross-functional leaders; mapped their top process inefficiencies and potential AI use cases.
• Landscape Assessment: Documented current-state workflows, tools, and pilots; identified gaps and duplication.
• Prioritization: Developed an initial backlog of AI/automation use cases with impact/feasibility scoring.
• Early Delivery: Designed and deployed at least 1–2 small-scale automations that demonstrate visible value (e.g., time savings, error reduction).
• Team Alignment: Established operating rhythm with developers (standups, backlog grooming, delivery cadence).

4-6 Months

• Project Delivery: Successfully launched 2–3 high-value pilot projects with measurable ROI (e.g., 20% reduction in manual effort for targeted workflows).
• Documentation & Standards: Created playbooks and standardized documentation for workflows, ensuring reproducibility and scale.
• Technology Scouting: Completed evaluation of emerging AI/automation platforms; delivered recommendation and piloted at least one new technology.
• Enterprise Engagement: Built an internal network of functional “AI champions” in 3–4 departments to drive adoption and evangelism.
• Kicked off an AI Council to share ideas across teams
• GenAI team enablement through Town Hall segments and other forums
• Performance Tracking: Deployed adoption and impact dashboards; established KPIs to track efficiency gains, hours saved, and business outcomes.

7 Months & beyond

• Transformational Outcomes: Delivered at least 1–2 enterprise-level projects that unlocked step-change efficiency (e.g., automated GTM lead management, GenAI-enabled reporting, compliance automation).
• Roadmap Execution: Published and executed against a multi-year AI/automation roadmap with clear priorities, ROI expectations, and resource planning.
• Enterprise Enablement: Launched ongoing enablement program (training, playbooks, workshops) empowering business teams to self-identify and adopt AI solutions.
• Cultural Impact: Positioned AI Ops as a trusted transformation partner; measurable increase in cross-functional adoption and demand for AI workflows.
• Sustained ROI: Demonstrated consistent, quantifiable business outcomes (e.g., % reduction in cycle times, cost avoidance, productivity gains).
• Team Growth: Built a high-performing team culture with developers, fostering experimentation and continuous improvement.