5+ years designing, developing, and deploying GenAI solutions from ideation to production.
5+ years delivering high-value use cases through hands-on engineering.
5+ years guiding teams in leveraging enterprise AI platform capabilities effectively.
5+ years driving adoption of enterprise AI platforms like Azure AI and AWS Bedrock.
5+ years translating platform capabilities into practical implementation patterns.
5+ years aligning use cases with enterprise AI strategy and governance requirements.
5+ years serving as a liaison between centralized AI platform teams and engineering teams.
5+ years delivering training sessions and technical guidance to engineering teams.
5+ years developing enablement materials such as documentation and playbooks.
Bachelor's degree in Computer Science or equivalent experience.
Responsibilities
Accelerate adoption of enterprise AI platforms across Lines of Business (LOBs).
Enable rapid delivery of high-value AI solutions aligned with organizational standards.
Ensure solutions are scalable, secure, and compliant with responsible AI practices.
Translate platform capabilities into reusable implementation patterns for teams.
Guide engineering teams in effective use of enterprise AI platform capabilities.
Deliver training sessions and workshops to upskill teams on GenAI techniques.
Develop comprehensive enablement materials including documentation and quick-start guides.
Benefits
Opportunity to work with cutting-edge AI technologies.
Collaborative environment with cross-functional teams.
Focus on professional development and upskilling.
Access to resources for continuous learning and innovation.
Engagement in high-impact projects that drive enterprise value.
Full Job Description
JOB SUMMARY The Enablement Engineer is a senior hands-on engineering role responsible for accelerating adoption of enterprise AI platforms across Lines of Business (LOBs). This role is aligned to a designated CIO organization and is accountable for enabling rapid delivery of high-value AI Solutions. This position combines deep technical expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI with a focus on solution delivery, reusable patterns, and enterprise enablement. The role ensures solutions are scalable, secure, and compliant with organizational standards for responsible AI.
Required Qualifications • Minimum 5+ years of experience designing, developing, and deploying GenAI solutions from ideation through production • Minimum 5+ years of experience delivering of high-value use cases through hands-on engineering and solutioning • Minimum 5+ years of experience guiding teams in leveraging enterprise AI platform capabilities effectively • Minimum 5+ years of experience driving adoption of enterprise AI platforms (e.g., Azure AI, AWS Bedrock, internal platforms) • Minimum 5+ years of experience translate platform capabilities into practical implementation patterns • Minimum 5+ years of experience aligning use cases to enterprise AI strategy, standards, and governance requirements • Minimum 5+ years of experience serving as a liaison between centralized AI platform teams and CIO-aligned engineering teams • Minimum 5+ years of experience delivering training sessions, workshops, and technical guidance to engineering teams • Minimum 5+ years of experience developing enablement materials including documentation, playbooks, and quick-start guides • Minimum 5+ years of experience upskilling teams on GenAI techniques such as prompt engineering, RAG design, and orchestration frameworks • Bachelors in Computer Science or equivalent work experience
