Sr. GenAI Tooling Engineer

Meritore Technologies is seeking a Senior GenAI Tooling Engineer to drive enterprise AI tooling strategy and implementation. The role involves evaluating AI engineering tools, leading platform integrations, and enhancing engineering productivity across a regulated environment.

Responsibilities:

• Evaluate emerging AI engineering tools and recommend platforms that improve engineering productivity, AI quality, governance, observability, and operational excellence
• Conduct technical assessments, proof of concepts, and platform evaluations
• Support business cases, platform roadmaps, and tool rationalization efforts
• Recommend enhancements that maximize engineering value while minimizing platform complexity
• Lead implementation, configuration, and lifecycle management of enterprise AI engineering platforms
• Initially own Jellyfish and Amplitude implementations, integrations, upgrades, and enterprise rollout
• Integrate platforms with Azure DevOps, GitHub, Jira, ServiceNow, Azure, identity services, RBAC, REST APIs, telemetry, and enterprise systems
• Develop reusable onboarding playbooks, automation, templates, and implementation standards
• Support engineering teams and applications during onboarding
• Develop onboarding processes, documentation, training, and self-service capabilities
• Partner with engineering teams to maximize platform adoption and engineering productivity
• Drive change management activities and continuously improve developer experience
• Monitor platform health, availability, utilization, and operational performance
• Coordinate incident management, vendor escalations, upgrades, release planning, and maintenance
• Optimize platform configuration, licensing, performance, scalability, and operational maturity
• Automate repetitive platform administration activities wherever practical
• Design and develop engineering dashboards, executive scorecards, operational KPIs, adoption metrics, utilization analytics, ROI dashboards, and business-value reporting
• Provide actionable insights that improve engineering effectiveness, platform investments, and decision making
• Analyse engineering trends and identify opportunities to improve platform usage and productivity
• Continuously evaluate new capabilities and recommend platform enhancements
• Optimize integrations, workflows, licensing, feature adoption, and operational processes
• Develop reusable engineering assets that improve implementation speed and consistency
• Partner with AI Engineering, AI Automation, AI QE, AI AppOps, Enterprise Architecture, Security, Cloud Engineering, Product teams, and Vendors
• Collaborate with AI Infrastructure & Cloud and Enterprise Data & Analytics Platform teams to ensure seamless integrations while respecting ownership boundaries