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.
How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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