| Job Description: |
AI Tooling Experts are responsible for designing, implementing, and governing the enterprise AI tooling ecosystem that enables scalable development, deployment, and operation of AI solutions. This role focuses on building standardized, reusable, and governed tools, integrations, and platforms to accelerate AI adoption across the organization.
They act as the bridge between AI engineering teams, platform teams, and enterprise architecture to ensure tools are secure, scalable, and aligned with enterprise standards.
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Key Responsibilities
1. AI Tooling & Platform Enablement
• Define and implement AI tooling frameworks, standards, and lifecycle management practices (selection, onboarding, versioning, deprecation).
• Build and manage tooling integrations across AI platforms, data platforms, and enterprise systems.
• Enable developer access to models, tools, orchestration frameworks, and APIs through standardized mechanisms.
2. Tool Integration & Ecosystem Development
• Develop and maintain connectors, APIs, and integration libraries for enterprise systems and AI services.
• Support integration of LLMs, agent frameworks, orchestration engines, and vector/knowledge systems.
• Ensure interoperability between tools and adherence to enterprise architecture guidelines.
3. Governance, Security & Compliance
• Establish tool governance models including access control, sandboxing, approval workflows, and auditability.
• Align tooling practices with data privacy, cybersecurity, and regulatory requirements.
• Implement versioning, monitoring, and lifecycle controls for AI tools.
4. Observability & Evaluation Tooling
• Implement tooling for monitoring AI systems (prompt tracking, model outputs, tool usage, agent flows).
• Develop frameworks for evaluation, A/B testing, and performance tuning of AI solutions.
• Support traceability and audit logs for enterprise-grade AI systems.
5. Developer Experience & Enablement
• Contribute to internal developer platforms and portals to simplify AI adoption.
• Define onboarding workflows, documentation, and reusable templates for teams.
• Enable self-service access to AI tools and services with guardrails.
6. Collaboration & Stakeholder Alignment
• Partner with engineering, architecture, security, and business teams to align tooling decisions.
• Work closely with AI engineers and platform teams to improve delivery speed and standardization.
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Key Skills & Qualifications
Technical Skills
• Experience with AI/ML platforms, LLM tools, and agentic frameworks
• Strong knowledge of API integrations, microservices, and cloud platforms (Azure/AWS/GCP)
• Familiarity with MLOps / LLMOps / DevOps practices and CI/CD pipelines
• Exposure to RAG, vector databases, orchestration tools, and evaluation frameworks
• Understanding of observability, telemetry, and monitoring tools
Functional & Leadership Skills
• Ability to design scalable enterprise tooling ecosystems (not point solutions)
• Strong problem-solving and cross-functional collaboration skills
• Experience in governance, compliance, and secure AI implementations
• Capability to balance innovation (new tools) with enterprise standardization
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Success Metrics
• Adoption rate of standardized AI tools across teams
• Reduction in development time and rework through reusable tooling
• Improved governance, compliance, and audit readiness
• Enhanced developer productivity and platform scalability
• Stability and observability of AI systems in production
Role Descriptions: AI Tools SME
Skills: AI & Gen AI - Products & Tools
Experience Required: 8-10
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