Digital and IT Technical Specialist - Lead AI Platform Enablement Engineer

The Lead AI Platform Enablement Engineer is responsible for enabling the successful delivery, integration, and operationalization of AI and GenAI solutions across Parker by serving as the technical bridge between application development teams, Enterprise AI Platform teams, Cyber Security, Enterprise Architecture, Data & Analytics, and business stakeholders. This role does not own the enterprise AI infrastructure, on-premise AI environment, Azure AI administration, or core AI application development; instead, it ensures development teams can effectively consume approved AI platforms, services, patterns, and resources in a secure, scalable, supportable, and governed manner.

Combining expertise in application architecture, DevSecOps, cloud platforms, AI engineering practices, integration patterns, and LLMOps, this role partners closely with AI infrastructure owners and application development teams to translate AI use cases into executable technical approaches. Scope includes AI project intake support, platform onboarding coordination, environment readiness, Infrastructure as Code (IaC) templating, integration design, AI service consumption patterns, CI/CD and release enablement, prompt and model lifecycle practices, AI FinOps and token cost management, AI observability, security review support, reusable templates, technical documentation, and operational readiness.

The Lead AI Platform Enablement Engineer accelerates AI adoption by reducing friction between platform teams and developers, establishing repeatable implementation patterns, supporting responsible AI and security requirements, and helping Parker deliver AI-powered business solutions with speed, quality, compliance, and enterprise scalability. This role reports to the Digital & IT Team Lead and is recognized as a subject matter expert in AI platform enablement, DevSecOps, enterprise integrations, AI solution delivery, and modern software development practices.

Responsibilities

Essential Functions:

• Serve as the primary technical liaison between Enterprise AI Platform teams, AI infrastructure teams, Application Development teams, Cyber Security, Enterprise Architecture, Data & Analytics, and business stakeholders.

• Facilitate onboarding of AI and GenAI projects onto approved Parker AI platforms, including coordination of access, environments, connectivity, authentication, authorization, APIs, data access patterns, and deployment readiness.

• Translate business and technical AI use cases into executable solution designs, platform requirements, integration patterns, security considerations, and delivery plans with clear acceptance criteria.

• Define and maintain reusable AI solution reference architectures, design patterns, implementation guides, onboarding checklists, runbooks, and technical standards for application teams.

• Partner with development teams to determine appropriate AI implementation approaches, including GenAI, Retrieval Augmented Generation (RAG), AI agents, copilots, workflow automation, API-based AI services, and integration with approved enterprise AI capabilities.

• Support AI DevOps and LLMOps practices, including CI/CD pipeline enablement, prompt lifecycle management, model/service versioning concepts, automated testing, release management, monitoring, rollback planning, and operational readiness.

• Collaborate with Enterprise AI Platform and Infrastructure teams to ensure application teams can effectively consume Azure AI services, on-premise AI capabilities, approved model endpoints, vector search, AI gateways, and enterprise integration services.

• Provide technical guidance for AI solution architecture reviews, ensuring proposed designs are scalable, secure, reliable, maintainable, and aligned with Parker technology standards, and optimized for AI FinOps (including token usage tracking, quota management, model caching, rate limiting, and cost attribution).

• Review AI-enabled application designs for security, privacy, compliance, data protection, identity and access management, secrets handling, logging, monitoring, and operational supportability.

• Assist teams with defining AI evaluation approaches, including automated eval pipelines (e.g., assessing groundedness, context recall, toxicity, and hallucination rates), OpenTelemetry tracing, prompt testing, response quality assessment, guardrails, human review requirements, and production-readiness criteria.

• Develop and maintain enterprise Infrastructure as Code (IaC) modules (e.g., Bicep, Terraform) and GitHub/Azure DevOps pipelines to enable self-service, secure, and automated provisioning of approved AI landing zones for application teams.

• Establish architecture patterns and security guardrails for emerging AI Agent workflows (e.g., Semantic Kernel, LangChain/LangGraph), ensuring standard patterns for tool execution, memory management, and human-in-the-lead controls.

• Partner with Cyber Security and governance stakeholders to support responsible AI practices, risk identification, mitigation planning, auditability, and adherence to Parker AI governance and cybersecurity expectations.

• Create and maintain architectural documentation, technical decision records, integration diagrams, support models, deployment guides, and reusable templates for AI-enabled solutions.

• Support proof-of-concepts, pilots, hackathons, vendor evaluations, and emerging technology assessments by evaluating technical feasibility, integration complexity, security implications, platform fit, and long-term supportability.

• Help development teams troubleshoot AI platform integration issues, authentication and API challenges, deployment constraints, performance bottlenecks, observability gaps, and operational incidents.

• Promote standardization and reuse across AI projects by identifying common patterns, shared components, automation opportunities, and enterprise-ready implementation practices.

• Proactively anticipate changes in AI technologies, enterprise platform capabilities, security requirements, and development practices; provide recommendations to leadership and help implement improvements.

• Build trust with business partners, platform teams, development teams, and stakeholders by translating complex AI and platform concepts into clear technical and non-technical language.

• Demonstrate a high degree of emotional intelligence, organizational awareness, ownership, and collaboration while working across matrixed teams that may not directly report to the role.

• Ability to travel as needed.

• Available to provide after-hours technical support as needed.

• 4-year University degree in Computer Science, Information Technology, Engineering, Data Science, or related discipline.

• Eight or more years of experience in Information Technology, software engineering, cloud engineering, platform engineering, DevOps, solution architecture, enterprise integrations, or related technical disciplines.

• Experience working across application development, infrastructure, security, architecture, and business teams to deliver enterprise-scale technology solutions.

• Strong understanding of modern application architecture, cloud-native design, APIs, integration patterns, authentication, authorization, and secure software delivery practices.

• Experience with Microsoft Azure services and cloud platform concepts, including identity, networking, application hosting, API integration, monitoring, Infrastructure as Code (IaC using Bicep or Terraform) and cost-conscious design.

• Hands-on experience with DevOps and DevSecOps practices, including source control, CI/CD pipelines, automated testing, release management, deployment automation, and operational monitoring.

• Working knowledge of AI and GenAI concepts, including large language models, Retrieval Augmented Generation, prompt engineering, AI agents, embeddings, vector search, model endpoints, copilots, and AI-assisted user experiences.

• Familiarity with AI platform capabilities such as Azure AI, Azure OpenAI, Azure AI Search, Azure AI Foundry, model gateways, vector databases, enterprise AI APIs, and on-premise AI platform consumption patterns.

• Understanding of LLMOps and AI operational practices, including prompt lifecycle management, AI evaluation, model/service versioning, observability, testing, monitoring, guardrails, and production-readiness criteria.

• Ability to design and document AI solution patterns, platform integration approaches, security boundaries, data flow diagrams, API contracts, and operational support models.

• Security-by-design mindset with experience applying secure SDLC, DevSecOps, access control, secrets management, data protection, logging, vulnerability management, and compliance practices.

• Awareness of responsible AI practices, including privacy, safety, bias mitigation, prompt injection considerations, auditability, human oversight, and appropriate use of enterprise-approved AI tools.

• Experience supporting development teams through technical consulting, design reviews, troubleshooting, reusable templates, standards, documentation, and coaching.

• Ability to evaluate vendor solutions, emerging AI technologies, and platform capabilities for technical feasibility, enterprise fit, integration complexity, risk, scalability, and supportability.

• Strong communication, collaboration, and stakeholder engagement skills with the ability to work effectively with technical teams, business partners, vendors, Cyber Security, Enterprise Architecture, and leadership.

• Demonstrated ability to lead through influence in a matrixed organization, drive alignment across teams, remove delivery blockers, and promote adoption of enterprise standards.

• Experience in Agile delivery practices and ability to apply those processes to everyday work.

• Ability to create high-quality technical documentation, architecture diagrams, runbooks, implementation guides, and executive-level summaries.

• Preferred certifications may include Microsoft AI-102 Azure AI Engineer, AZ-305 Azure Solutions Architect, AZ-204 Azure Developer, Azure Security Engineer, GitHub Actions, DevOps, cybersecurity, or architecture-related certifications.

• Preferred experience with GitHub Enterprise, Azure DevOps, API Management, Kubernetes or containerized applications, Infrastructure as Code, application observability tools, and enterprise integration platforms.

Key Skills Needed

• AI platform enablement and AI solution integration

• DevOps, DevSecOps, and LLMOps practices

• Azure cloud and enterprise platform experience

• GenAI, RAG, prompt engineering, and AI agent concepts

• API integration, identity, access, and secure architecture

• AI governance, responsible AI, and risk-aware delivery

• Infrastructure as Code (IaC) & automated platform provisioning (Bicep / Terraform)

• AI FinOps, token usage tracking, and cost optimization

• Technical documentation and reusable architecture patterns

• Cross-functional leadership between developers, infrastructure, security, and business teams

• Vendor and platform technical evaluation

• Strong communication and influence without direct authority
• Provides hands-on ownership of Akamai security platforms and supports additional security technologies.

This position requires strong operational discipline, deep understanding of web application threats, and the ability to balance security enforcement with availability and customer experience in production environments.

Parker Hannifin

Parker Hannifin is a Fortune 250 global leader in motion and control technologies. For more than a century, we’ve enabled engineering breakthroughs that make energy cleaner, transportation safer, medical treatments more effective, and manufacturing more efficient.

With empowered team members in more than 40 countries, Parker serves customers across aerospace & defense, energy, HVAC & refrigeration, in-plant & industrial equipment, off-highway and transportation.

Our scale is global, but our purpose is personal. We enable breakthroughs that improve lives, strengthen communities and create a brighter future.

Our Purpose - Enabling Engineering Breakthroughs that Lead to a Better Tomorrow - comes to life through our people-first culture where teamwork drives performance, inclusion fuels innovation and growth is encouraged. This environment fosters collaboration and empowers team members from engineering and manufacturing to finance, supply chain, human resources, information technology and beyond.

By combining deep expertise with an entrepreneurial spirit, we help customers succeed in markets that demand performance, reliability, and sustainability.

As we look to the future, Parker is advancing initiatives in energy efficiency and sustainability while developing the next generation of talent and leaders to engineer a better tomorrow.