Lead GenAI SaaS / Platform Engineer

Accountabilities • GenAI Platform Administration: Own the end-to-end administration, configuration, governance, and lifecycle management of enterprise generative AI platforms, including ChatGPT Enterprise, Claude, and other internal AI solutions.

• Platform Architecture & Scalability: Design and maintain scalable SaaS architectures that support enterprise-wide AI adoption, ensuring platform reliability, performance, and operational efficiency.

• Integrations & Extensibility: Develop and implement Model Context Protocol (MCP) connectors, REST API integrations, and secure data pipelines to connect LLM platforms with enterprise applications, systems, and business tools.

• Identity & Access Management: Establish and maintain enterprise-grade authentication and authorization frameworks using SAML 2.0, SCIM provisioning, OAuth, and role-based access control (RBAC), leveraging Okta and Microsoft Entra ID.

• Security & AI Governance: Define and enforce security policies, data privacy controls, compliance requirements, and responsible AI usage guidelines to ensure secure and controlled adoption of generative AI technologies.

• Automation & Scripting: Develop automation scripts and operational workflows using Python or PowerShell to streamline user provisioning, platform configuration, usage monitoring, and policy enforcement.

• Platform Monitoring & Reliability: Monitor platform health, availability, performance, and usage across enterprise environments, identifying operational risks and implementing preventive improvements.

• Incident & Escalation Management: Lead complex technical troubleshooting and Tier 3 incident escalations, ensuring timely resolution and minimizing service disruptions.

• Consumption & License Management: Monitor AI platform consumption, licensing metrics, user activity, and operational costs to optimize resource utilization and platform efficiency.

• Cloud Infrastructure Operations: Support reliable platform operations across AWS and Azure environments, ensuring appropriate logging, monitoring, security, and infrastructure integration.

• Cross-Functional Collaboration: Partner with Security, Workplace IT, endpoint engineering, and MDM teams to coordinate platform requirements and align SaaS architecture with enterprise technology standards.

• Continuous Improvement: Stay informed about emerging LLM technologies, AI integration standards, and SaaS engineering practices to continuously improve enterprise AI capabilities.

Requirements

• 8–12 years of professional experience in Enterprise SaaS Engineering, Cloud Infrastructure, Platform Engineering, or Enterprise Platform Administration.

• Strong hands-on experience designing, implementing, and managing enterprise SaaS platforms and complex technical environments.

• Identity & Access Management: Deep understanding of modern IAM architectures, including Okta, Microsoft Entra ID, Single Sign-On (SSO), SAML 2.0, SCIM provisioning, OAuth flows, and role-based access control (RBAC).

• Generative AI & LLM Platforms: Practical familiarity with enterprise generative AI platforms, LLM toolchains, AI integrations, and enterprise AI governance frameworks.

• Experience administering ChatGPT Enterprise, Claude Enterprise, or comparable enterprise AI platforms is a significant advantage.

• Knowledge of emerging AI integration standards, particularly Model Context Protocol (MCP), and their application in enterprise environments.

• Programming & Automation: Strong proficiency in Python or PowerShell, with demonstrated experience building automation scripts and managing operational workflows.

• API Integration: Hands-on experience with REST APIs, API authentication, system integrations, and secure data exchange between enterprise applications.

• Cloud Technologies: Solid understanding of AWS or Microsoft Azure, including cloud infrastructure, enterprise services, and platform operations.

• Monitoring & Incident Management: Experience with enterprise logging, monitoring, platform health management, troubleshooting, and complex incident resolution.

• Security & Compliance: Strong understanding of enterprise security principles, data privacy, access governance, and least-privilege security models.

• SaaS Operations: Experience managing platform configurations, user provisioning, licensing, consumption metrics, and enterprise software lifecycle activities.

• Collaboration: Ability to work effectively with cross-functional teams, particularly Security, Workplace IT, infrastructure, and endpoint engineering.

• Leadership & Communication: Strong problem-solving, organizational, and communication skills, with the ability to take technical ownership and guide enterprise platform initiatives.

• A proactive mindset, adaptability, and enthusiasm for learning emerging generative AI technologies are essential.

Benefits

• Fully remote working arrangement within India.

• Full-time employment opportunity.

• Opportunity to work on enterprise-scale generative AI platforms and emerging LLM technologies.

• Exposure to advanced AI solutions, including ChatGPT Enterprise, Claude, and MCP integrations.

• Opportunity to lead strategic initiatives in enterprise AI architecture, platform engineering, and governance.

• Professional growth through hands-on experience with modern SaaS platforms, cloud infrastructure, and enterprise security technologies.

• Collaborative environment involving cross-functional teams and global enterprise operations.

• Opportunity to influence AI adoption strategies and build scalable, secure, and innovative technology solutions.

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