AI, Enablement Engineer

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 workflowsdriving 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 skillsincluding experience collaborating with global and offshore teams.

Key Responsibilities:

AI Solution Design & Implementation

• Act as the technical owner and developer of AI-powered automation projectsfrom discovery through deliveryacross 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 solutionsoften 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 & ExperienceGuidelines

• Bachelors ormasters 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 lifecyclefrom 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.
• Demonstratedproficiencyin time and project management as well as ability to handle priority setting and ability to resolve prioritization conflicts

• Ability to travel 25-30% isrequired.

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 acustomer-focusedculture byanticipatingevolving needs and shaping solutions that deliver long-term value.

Strategic:Drives organizational impact by usingdatato derive insights that inform near-term and mid-range goals

Innovation for Impact:Influences innovation throughdemonstratingbold thinking and experimentation in own work and coaching others to do the same.

Inspiring:Demonstratespurpose-driven impact throughexpertiseand collaboration.

Builds Extraordinary Teams:Drives impact through collaboration and influence by fostering trust sharingexpertise and aligning efforts across teams.

Courageous:Influences and leads by example throughactionand integritymoves quickly toward goals tackles challenges head-on and encourages open sharing of ideas without fear.

Delivers Results:Leads complex initiatives to successful completion withhigh standards precision and urgency.

Adaptable:Appliesrigorand stays true to process while fostering adaptability within the team.

Lead with FBS:Embraces FBSand models lean principles by mentoring peers and influencingteams andgoing toGembafor first-hand insights.