AI Enablement Engineer

Accountabilities:

• • Establish a safe, scalable, and repeatable AI enablement framework, defining where AI solutions should live, who can access them, and how they should be governed and managed.
  • Build AI-powered workflows, agents, integrations, and internal productivity solutions that address real business needs across multiple functions.
  • Develop and maintain MCP integrations, shared agents, agent identity management, and connections with enterprise SaaS and commercial systems.
  • Partner directly with functional leaders and subject-matter experts to understand existing workflows, identify inefficiencies, and design practical AI-enabled improvements.
  • Turn successful AI use cases into reusable templates, skills, agent specifications, and implementation patterns that other teams can adopt independently.
  • Collaborate with Engineering to develop custom solutions and integrations where existing tools cannot address business or technical requirements.
  • Create scalable enablement programs, including AI literacy initiatives, office hours, documentation, and internal AI champion networks.
  • Establish and maintain standards for secure authentication, access management, integrations, retrieval, agent development, and AI usage.
  • Develop continuous visibility into AI usage and costs, helping Finance identify redundant tools, shadow AI, and opportunities for optimization.
  • Improve AI economics through techniques such as prompt caching, model routing, workflow optimization, and more efficient agent design.
  • Diagnose business problems, scope and sequence technical initiatives, manage expectations, and deliver solutions that achieve measurable improvements.
  • Act as a technical advisor and internal consultant, helping stakeholders understand AI capabilities, limitations, implementation considerations, and appropriate use cases.

  Requirements:

  • 5+ years of hands-on experience as a Systems Engineer, Solutions Engineer, IT Engineer, or similar technical role within a SaaS or cloud-native organization.
  • Demonstrated experience deploying, optimizing, and supporting AI tools or AI-enabled workflows at organizational scale.
  • Strong technical range, including scripting and integration development using Python, TypeScript, and/or shell.
  • Working knowledge of software development lifecycle fundamentals, API integrations, secure authentication, retrieval systems, and enterprise SaaS environments.
  • Experience with MCP, AI agents, agent frameworks, LLM-based applications, or comparable emerging AI technologies.
  • Ability to quickly learn unfamiliar technologies and apply them effectively to new technical and business problems.
  • Strong consulting mindset, with the ability to diagnose the underlying business problem before determining the appropriate technical solution.
  • Excellent communication skills and the ability to work effectively with technical and non-technical stakeholders, from individual contributors to senior executives.
  • Ability to translate vague requests such as workflow inefficiencies or repetitive tasks into practical, working AI-enabled solutions.
  • Strong understanding of prioritization, sequencing, stakeholder management, and communicating technical trade-offs.
  • A collaborative, patient, and enablement-focused mindset, with a preference for building scalable solutions rather than becoming a bottleneck for individual requests.
  • Strong ownership and initiative, with the ability to work independently while partnering effectively across a distributed organization.
  • Commitment to responsible AI adoption, including appropriate attention to security, access, privacy, governance, and cost management.

  Benefits:

  • Fully remote work environment with flexibility and trust around how you manage your schedule.
  • Competitive compensation aligned with the impact and scope of the role.
  • Equity participation, providing an opportunity to share in the organization's growth.
  • Comprehensive employee benefits.
  • Flexible vacation policy.
  • Paid sabbatical after 5 years.
  • Health and wellness stipend supporting physical and mental well-being.
  • Technology and learning stipend for conferences, books, courses, and professional development.
  • Company-wide offsites and smaller team gatherings designed to strengthen connections across the distributed workforce.
  • Opportunity to work at the intersection of AI, LLMs, agents, automation, and enterprise technology.
  • Significant autonomy and ownership as the first dedicated AI Enablement Engineer, with the opportunity to establish foundational practices and systems.
  • Inclusive, collaborative culture focused on ownership, teamwork, continuous learning, self-awareness, and respectful communication.