AI Product Pilots Technical Lead (AI Platforms)
About The Position
The Product Pilots Technical Lead (AI Platforms) is responsible for evaluating, recommending, and ensuring that new AI platforms meet enterprise requirements, and are pilot and deployment ready through rigorous technical evaluation, structured pilot design, deployment readiness, and controlled implementation. This role focuses on validating whether AI products (e.g., Microsoft Copilot and similar products) offer performant and value-added capabilities; are secure; are technically, operationally, and organizationally ready for pilot and scaled rollout; and are DevSecOps and end-user supported. The position plays a critical role in translating pilot outcomes into deployment readiness decisions, ensuring that platforms meet enterprise standards for integration, security, performance, and supportability before broader adoption. The Technical Lead partners with IT, Business, Security, Legal, Compliance and other stakeholders and vendors to reduce risk and accelerate successful AI deployment.
Requirements
- Experience leading enterprise software deployments, pilots, or production readiness assessments.
- Strong understanding of cloud platforms, AI technologies, and enterprise system integration.
- Experience with deployment readiness, release management, or production support models.
- Knowledge of IT governance, security, and compliance requirements.
- Strong analytical, problem-solving, and stakeholder communication skills.
Responsibilities
- Conduct deep technical evaluations of AI platforms, including architecture, integration capabilities, features/capabilities, data handling, system performance, data security, and more.
- Build on and establish evaluation frameworks and test cases aligned to enterprise deployment requirements.
- Validate platform compatibility with existing infrastructure, identity systems, and enterprise tools.
- Assess reliability, maintainability, security, and support requirements for production usage.
- Design pilot programs specifically to test deployment readiness for 3rd party AI platforms in real-world scenarios.
- Define pilot scope, success criteria, and test cases that simulate production conditions and usage patterns.
- Ensure pilots generate the data needed to make informed scale decisions (e.g., capabilities, performance, adoption, support load, risk exposure).
- Align pilot objectives with AI Roadmap.
- Navigate pilots through enterprise approval processes (IT, Legal, Security, Compliance) with a focus on production deployment requirements.
- Ensure AI platforms meet all data privacy, security, and regulatory standards prior to scaling.
- Evaluate risks related to AI model behavior, data exposure, and operational controls.
- Coordinate end-to-end pilot deployment, including provisioning, environment configuration, and system integration.
- Partner with IT service providers and vendor to implement solutions in alignment with production-like standards.
- Provide technical oversight and hands-on support to ensure stable, reliable pilot execution.
- Monitor pilot environments to identify issues impacting future deployment viability.
- Lead end-to-end assessment of AI platform readiness for enterprise deployment, including technical, operational, and governance dimensions.
- Define and evaluate deployment readiness criteria such as scalability, integration maturity, security posture, support model, and user adoption readiness.
- Identify gaps, risks, and dependencies that could impact production deployment and develop mitigation strategies.
- Provide clear go/no-go recommendations for scaling based on pilot results and readiness benchmarks.
- Serve as the central liaison between IT, control owners, business stakeholders, and vendors.
- Communicate readiness status, risks, and requirements clearly to both technical and non-technical audiences.
- Enable stakeholders to understand what is required to move from pilot to production.
- Develop and maintain deployment readiness frameworks, checklists, and pilot playbooks.
- Standardize methodologies for evaluating and preparing AI platforms for scale.
- Capture lessons learned to continuously improve deployment readiness processes.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
