Lead GenAI SaaS / Platform Engineer
New
J
JobgetherEnterprise AI
Fully remote working arrangement within India.Full-TimeLead
Salary not disclosed
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Job Details
- Experience
- 8–12 years of professional experience
- Required Skills
- PythonRESTful APIs
Requirements
- Bring 8–12 years of professional experience in Enterprise SaaS Engineering, Cloud Infrastructure, Platform Engineering, or Enterprise Platform Administration.
- Have hands-on experience designing, implementing, and managing enterprise SaaS platforms and complex technical environments.
- Understand IAM architectures, including Okta, Microsoft Entra ID, SSO, SAML 2.0, SCIM provisioning, OAuth flows, and RBAC.
- Have practical familiarity with enterprise generative AI platforms, LLM toolchains, AI integrations, and enterprise AI governance.
- Have experience administering ChatGPT Enterprise, Claude Enterprise, or comparable platforms as an advantage.
- Understand emerging AI integration standards, particularly Model Context Protocol (MCP), and their enterprise use.
- Be proficient in Python or PowerShell and experienced in building automation scripts and operational workflows.
- Have hands-on experience with REST APIs, API authentication, system integrations, and secure data exchange.
- Understand AWS or Microsoft Azure, including cloud infrastructure, enterprise services, and platform operations.
- Have experience with enterprise logging, monitoring, platform health management, troubleshooting, and complex incident resolution.
- Understand enterprise security, data privacy, access governance, and least-privilege security models.
- Have experience managing platform configurations, user provisioning, licensing, consumption metrics, and enterprise software lifecycles.
- Work effectively with cross-functional Security, Workplace IT, infrastructure, and endpoint engineering teams.
Responsibilities
- Own administration, configuration, governance, and lifecycle management of enterprise generative AI platforms, including ChatGPT Enterprise, Claude, and internal AI solutions.
- Design and maintain scalable SaaS architectures for enterprise AI adoption, reliability, performance, and operational efficiency.
- Develop MCP connectors, REST API integrations, and secure data pipelines connecting LLM platforms to enterprise applications and business tools.
- Establish authentication and authorization frameworks using SAML 2.0, SCIM, OAuth, and RBAC with Okta and Microsoft Entra ID.
- Define and enforce security policies, data privacy controls, compliance requirements, and responsible AI usage guidelines.
- Build Python or PowerShell automation for provisioning, platform configuration, usage monitoring, and policy enforcement.
- Monitor platform health, availability, performance, and usage, and implement preventive improvements.
- Lead complex troubleshooting and Tier 3 incident escalations.
- Track AI platform consumption, licensing, user activity, and operational costs.
- Support platform operations across AWS and Azure, collaborating with Security, Workplace IT, endpoint engineering, and MDM teams.
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