AI, Enablement Engineer

Provation is a leading provider of healthcare software and SaaS solutions for clinical productivity and care coordination. The AI Enablement Engineer leads the delivery and scaling of AI-powered automation solutions across multiple business units, focusing on embedding AI into operational workflows to drive productivity and efficiency improvements.

Responsibilities:

• Act as the technical owner and developer of AI-powered automation projects—from discovery through delivery—across internal business domains (e.g. finance, operations, HR, customer support, product development)
• Translate ambiguous business problems into concrete AI/ML opportunities and deliver working solutions using tools like large language models, intelligent agents, workflow automation, and custom software integrations
• Build prototypes and minimum viable solutions (MVS), demonstrate ROI, and work with engineering or ops teams to scale or productionize
• Engage directly with business stakeholders, SMEs, and process owners to identify high-impact opportunities for AI enablement
• Collaborate with global engineering, data, and automation teams to deliver and support deployed solutions—often working with offshore counterparts
• Serve as a technical liaison across functions, ensuring solutions meet business needs, compliance standards, and technical best practices
• Create enablement artifacts (templates, documentation, reusable code, training resources) to allow teams to self-sustain and expand AI usage after the initial implementation
• Provide mentorship and onboarding support to internal teams inheriting automation frameworks or tools
• Design playbooks and re-usable modules that accelerate repeat adoption across other business units
• Establish a scalable model for rolling out AI automation solutions across business centers: build → enable → transition → replicate
• Drive consistent alignment to enterprise standards for responsible AI usage, data access, and compliance
• Influence tooling and platform decisions to ensure long-term sustainability and extensibility of AI-driven workflows

Requirements:

• Bachelor's or master's degree in Computer Science, Data Science, or related field
• 5-8 years of experience in software engineering, systems engineering, or automation development, preferably across multiple domains
• Demonstrated experience building and deploying AI/ML or automation solutions using tools such as Python, cloud services (AWS/GCP/Azure), REST APIs, orchestration platforms, or GenAI APIs (e.g. OpenAI, Bedrock, Azure OpenAI)
• Strong communication and stakeholder engagement skills; able to translate business needs into technical requirements and vice versa
• Proven success working across cross-functional and globally distributed teams, including coordination with offshore partners or delivery centers
• Ability to take ownership of the entire AI solution lifecycle—from problem framing to deployment to handoff
• Familiarity with enterprise SDLC, DevOps practices, security, and compliance constraints in complex environments
• Self-sufficient and self-starter who is able to apply solid thought processes to breakdown problems and complex situations into workstreams/actions that will drive impact and value
• Able to quickly learn and master FBS tools
• Demonstrated proficiency in time and project management, as well as ability to handle priority setting and ability to resolve prioritization conflicts
• Ability to travel 25-30% is required
• Experience designing intelligent automation in business process areas (e.g. document processing, ticket triage, reporting workflows)
• Knowledge of prompt engineering, agent frameworks, or LLM orchestration patterns is a strong plus
• Familiarity with MLOps or model lifecycle management tools is helpful but not required
• Experience working in organizations with federated operating models or shared services