AI Enablement Engineer

Overview

The AI Enablement Engineer leads the delivery and scaling of AI-powered automation solutions across multiple internal business units. This is a technical and strategic role focused on embedding AI into real-world operational workflows—driving measurable productivity, quality, and efficiency improvements across the enterprise.

This role partners closely with internal stakeholders to understand business needs, rapidly builds and deploys AI-enabled solutions, and establishes repeatable patterns that other teams can adopt. The work of this role will span engineering, product, operations, and business domains, creating the “flywheel” that accelerates AI adoption across departments. Once solutions are established and teams are enabled, this colleague will transition to new problem areas and help replicate success globally.

This role is ideal for a software or systems engineer with deep technical acumen, strong business intuition, and excellent communication skills—including experience collaborating with global and offshore teams.

Key Responsibilities

AI Solution Design & Implementation

• 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.

Cross-Functional Collaboration & Execution

• 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.

Enablement & Knowledge Transfer

• 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.

Scaling AI Across the Enterprise

• 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.

Required Qualifications

Education & Experience Guidelines

• 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.

Other Preferred Knowledge, Skills, Abilities Or Certifications

• 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.

Fortive 9 Behaviors By Level

Influencing & Mentoring

• Customer Obsessed: Champions a customer-focused culture by anticipating evolving needs and shaping solutions that deliver long-term value.
• Strategic: Drives organizational impact by using data to derive insights that inform near-term and mid-range goals.
• Innovation for Impact: Influences innovation through demonstrating bold thinking and experimentation in own work and coaching others to do the same.
• Inspiring: Demonstrates purpose-driven impact through expertise and collaboration.
• Builds Extraordinary Teams: Drives impact through collaboration and influence by fostering trust, sharing expertise, and aligning efforts across teams.
• Courageous: Influences and leads by example through action and integrity—moves quickly toward goals, tackles challenges head-on, and encourages open sharing of ideas without fear.
• Delivers Results: Leads complex initiatives to successful completion with high standards, precision, and urgency.
• Adaptable: Applies rigor and stays true to process while fostering adaptability within the team.
• Lead with FBS: Embraces FBS and models lean principles by mentoring peers and influencing teams, and going to Gemba for first-hand insights.

About Provation

Provation is a leading provider of healthcare software and SaaS solutions for clinical productivity, care coordination, quality reporting, and billing. Our purpose is to empower providers to deliver quality healthcare for all. Provation’s comprehensive portfolio spans the entire patient encounter, from pre-procedure through post-procedure, with solutions for physician and nursing documentation (Provation® MD, Provation® Apex, MD-Reports, Provation® endoPRO®, and Provation® MultiCaregiver), anesthesia documentation (#1 Best in KLAS Provation® iPro), patient engagement, surgical care coordination, quality reporting, and billing capture (Provation® SurgicalValet™), order set and care plan management (Provation® Order Set Advisor™ and Provation® Care Plans), and EHR embedded clinical documentation (Provation® Clinic Note). Provation has a loyal customer base, serving more than 5,000 hospitals, surgery centers, and medical offices, and 700 physician groups globally, including 19 of the top 20 U.S. hospitals. In 2021, Provation was acquired by Fortive Corporation, a Fortune 1000 company that builds essential technology and accelerates transformation in high-impact fields like workplace safety, engineering, and healthcare. For more information about our solutions, visit provationmedical.com and follow us on Twitter, Facebook, and LinkedIn. Our purpose at Provation is to empower providers to deliver quality healthcare for all. To deliver on this commitment, we’re guided by our core values – Provation has a culture of CARES: Community - We have a shared sense of improving healthcare, enriching the broader world we live in and serve. Accountability - We own it and get it done with integrity. Respect - We build diverse teams that collaborate and communicate with positive intent and trust. Excellence - We welcome new ideas as we innovate quality solutions. Service - We are passionate about putting customers first.

Key skills/competency

• AI Solution Design
• Automation Development
• Machine Learning Deployment
• Python Programming
• Cloud Services (AWS/GCP/Azure)
• REST API Integration
• Large Language Models (LLM)
• Stakeholder Management
• SDLC & DevOps
• Cross-Functional Collaboration