AI Enablement Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Enablement Engineer based in United States.

• 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.

• 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.

• 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.