Program Manager, AI & Innovation

DocuSign DocuSign · Enterprise · San Francisco, CA · Business/Sales Operations & Strategy

Program Manager for AI & Innovation at DocuSign, focusing on operationalizing AI at scale across the enterprise. The role involves managing the end-to-end AI experimentation lifecycle, building and iterating on prompts, workflows, and agents, and translating AI opportunities into program roadmaps. It requires a hands-on understanding of the LLM lifecycle, AI system design, and challenges unique to AI systems, with a focus on moving from experimentation to production-grade deployment.

What you'd actually do

  1. Orchestrate the end-to-end AI experimentation lifecycle, driving initiatives from initial prototyping and POC through pilot phases to production-grade monitoring and enterprise scale
  2. Build and iterate on prompts, workflows, and agents using no code agents, LLMs across Commerce, Sales, and Self-Service (.com) experiences, from ideation through production scale
  3. Translate ambiguous AI opportunities into clear program roadmaps, aligning model capabilities with business outcomes
  4. Partner with Product, Engineering, Technology and Data Science to operationalize and agentify workflows
  5. Leverage PMO tools and methodologies to implement and manage scope, timelines, risks, and resources

Skills

Required

  • 8+ years of experience of project management best practices and Agile methodology
  • Hands-on understanding of the LLM lifecycle
  • Prompt engineering and prompt optimization
  • Fine-tuning approaches and trade-offs
  • Evaluation methodologies (automated + human feedback loops)
  • AI system design and infrastructure
  • model APIs
  • vector databases
  • embeddings
  • orchestration frameworks
  • Experience managing challenges unique to AI systems
  • Working knowledge of Responsible AI, data governance, and privacy considerations in production environments
  • Experience working with enterprise systems (e.g., Salesforce, CPQ, billing platforms) and digital transformation initiatives
  • Demonstrated ability to move from AI pilots and experimentation to production-grade deployment
  • Bachelor’s Degree in Computer Science or related field or equivalent experience

Nice to have

  • Exceptional communication skills with the ability to influence senior executives and translate complexity into clarity
  • Experience leading AI/ML-driven product or platform initiatives in a SaaS environment
  • Exposure to AI tooling ecosystems (e.g., LLM platforms, orchestration frameworks, evaluation tools)
  • Background working closely with Data Science, ML Engineering, or Applied AI teams
  • Ability to simplify complex AI concepts for business stakeholders and drive adoption
  • Ability to quickly understand complex issues and develop or apply simplifying frameworks to facilitate broader organizational understanding, decision-making and action
  • Detail-oriented with excellent verbal, written, organizational, presentation and interpersonal communications skills

What the JD emphasized

  • shipping AI is fundamentally different from shipping traditional software
  • model drift
  • evaluation uncertainty
  • data governance
  • compute trade-offs
  • Responsible AI
  • data privacy
  • security
  • Prompt engineering and prompt optimization
  • Fine-tuning approaches and trade-offs
  • Evaluation methodologies (automated + human feedback loops)
  • AI system design and infrastructure
  • model APIs
  • vector databases
  • embeddings
  • orchestration frameworks
  • challenges unique to AI systems

Other signals

  • AI-first enterprise
  • operationalized at scale
  • shipping AI is fundamentally different
  • model drift, evaluation uncertainty, data governance, and compute trade-offs