Genai Tooling Engineer

Role: Sr. GenAI Tooling Engineer

Location: Eden Prairie, MN - 3 days/ week office

Roles and Responsibilities:

Develop and maintain Client's enterprise AI tooling strategy and roadmap aligned with the AI Development Lifecycle (AI-DLC), enterprise architecture, security, governance, product, and delivery priorities.

Identify tooling gaps, duplication, interoperability challenges, adoption barriers, operational risks, and consolidation opportunities across the AI ecosystem.

Recommend tooling investments, lifecycle decisions, optimization strategies, and rationalization opportunities to executive leadership. Establish long-term plans that support scalable AI platform growth and enterprise engineering productivity.

Define and execute the implementation roadmap for engineering productivity and product analytics tooling, including Jellyfish and Amplitude, as part of the broader AI tooling strategy. AI Tool Lifecycle Management & Standards

Own the enterprise lifecycle framework for AI tooling, including evaluation, onboarding, implementation, adoption, optimization, renewal, and retirement.

Take ownership of AI tooling implementation and lifecycle management for platforms such as Jellyfish and Amplitude, including hands-on configuration, integration, adoption, operationalization, optimization, and ongoing support.

Establish standards for AI tool intake, ownership, access management, onboarding, integration readiness, documentation, observability, operational support, lifecycle reviews, and retirement.

Design and build observability layers for AI tooling and analytics platforms to track adoption, usage patterns, workflow performance, integration health, data quality, reliability, and measurable business impact.

Maintain a comprehensive enterprise inventory of AI tools, capabilities, owners, users, licenses, integrations, vendors, costs, risks, controls, and operational status.

Ensure tooling governance aligns with enterprise security, compliance, and Responsible AI standards. Governance, Vendor Management & Enterprise Enablement

Partner with Architecture, Security, Infrastructure, Governance, Compliance, Procurement, Legal, Finance, Product, Engineering, Platform, and LLMOps/AIOps teams to align AI tooling with enterprise standards and business objectives.

Work across Product, Engineering, Data, Architecture, Security, Infrastructure, Platform, and Operations teams to drive tool integration, resolve technical dependencies, define implementation approaches, and ensure successful adoption of Jellyfish, Amplitude, and related AI tooling platforms.

Coordinate vendor engagement and platform partnerships, including vendor evaluations, support models, escalation processes, roadmap planning, contract renewals, and performance management.

Monitor AI tooling spends, license utilization, adoption trends, renewal schedules, operational risks, and cost optimization opportunities.

Facilitate enterprise intake, prioritization, and cross-functional review of AI tooling requests, implementation dependencies, lifecycle decisions, and operational readiness activities.

Serve as the central coordination point for enterprise AI tooling governance and lifecycle management.

Experience: - Min 8+ Years

Educational Qualifications: -

Engineering Degree BE/ME/BTech/MTech/BSc/MSc.

Technical certification in multiple technologies is desirable.

Skills: -

Mandatory skills

Minimum of seven (8+) years of progressive experience in technology, platform engineering, enterprise tooling, AI platforms, DevOps, engineering enablement, or related disciplines.

Demonstrated ability to lead cross-functional initiatives involving technology strategy, governance, platform operations, vendor management, and enterprise stakeholder engagement.

Ability to operate hands-on while also collaborating effectively across multiple technical teams to deliver integrated tooling solutions in complex enterprise environments.

Experience operating as a hands-on player-coach in a lean, fast-paced, evolving enterprise environment.

Experience within healthcare, payer, provider, clinical, life sciences, or other highly regulated industries.

Experience administering, configuring, or integrating enterprise engineering, DevOps, cloud, data, observability, governance, or productivity platforms.

Hands-on experience implementing, configuring, integrating, or managing engineering productivity, product analytics, observability, or AI tooling platforms such as Jellyfish, Amplitude, or similar tools.

Experience with platforms such as GitHub Enterprise, Azure DevOps, ServiceNow, Databricks, Microsoft Entra ID, model-provider platforms, or similar enterprise technologies.

Experience supporting AI delivery platforms, LLMOps, AIOps, AI Quality Engineering, prompt management, agentic AI tooling, model evaluation, or Responsible AI governance.

Experience with Internal D

Skills

GenAI Amplitude, Jellyfish, LLM, OpenAI, Azure, Python RAG Pipeline, AgenticAI 'AI Tooling Strategy & Roadmap.