Job Description

Job Summary

JD - We are looking for a hands-on Lead Engineer / Solution SME to support, implement, and scale Google Gemini Enterprise App across the enterprise. This role will own supporting L1,L2 & L3 issues related enterprise search and summarization, low-code/no-code agents, connectors onboarding, identity and access, custom mcp server, integration & Deployment, and AI security guardrails. The person will work closely with business, security, IAM, data, and application teams to deliver secure, permissions-aware, production-ready Gemini Enterprise App GCP Services-Focused Responsibilities Excellent in providing L1, L2 & L3 support for Gemini Enterprise App related issues. Own the full ServiceNow ticket lifecycle including triage, categorization, prioritization, resolution, and closure with no internal L1/L2/L3 handoff beyond this pair. Lead the architecture and rollout of Gemini Enterprise App for enterprise search, summarization, assistants, and agent-driven workflows across business functions. Design and implement permissions-aware search and retrieval across structured and unstructured enterprise content. Configure, manage & support prebuilt connectors for Google and third-party enterprise systems such as Confluence, Jira, SharePoint, ServiceNow, and other knowledge sources. Build custom mcp server: Develop & Deploy for non-standard enterprise systems and APIs, including data ingestion, indexing, metadata handling, ACL mapping, and synchronization design. Assist, Guide, Create, troubleshoot operationalize no-code / low-code agents using Agent Designer, including single-step and multi-step workflows, orchestration, and recurring task automation. Support onboarding and governance of Google-made, third-party, and internally built agents, including custom agents built by internal engineering teams. Define and implement identity and access strategies using Google Identity and Workforce Identity Federation, including SSO, group/claim mapping, access-controlled data sources, and user authorization models. Partner with IAM and security teams on OIDC/SAML federation, attribute mapping, group-based access, and SCIM-based provisioning where required. Establish best practices for prompt design, grounding, response quality, evaluation, and responsible AI adoption across enterprise use cases Work with business stakeholders to identify high-value use cases, prioritize rollout waves, and measure adoption, quality, and business impact. Create architecture standards, implementation playbooks, and operational runbooks for support and scale. Implement, Support GCP Model Armor to protect AI models and agents from adversarial threats, vulnerabilities, and misuse in production environments. Establish and refine generative AI evaluation frameworks to assess model performance, accuracy, bias, reliability, and alignment with business KPIs continuously. Define and implement comprehensive security strategies: enforce least privileged IAM, monitor agent activities, employ VPC Service Controls, and ensure data encryption and compliance with organizational policies. Must be proficient with Terraform, GITHUB Actions & in Python Language. Monitor and troubleshoot connectors health, performance, and security incidents using Google Cloud Operations and custom telemetry integrations. Document architecture designs, standard operating procedures, troubleshooting guides, and best practices for deploying and managing Gemini Enterprise in production. Required Skills and Expertise 8+ years of experience in cloud architecture, enterprise integration, platform engineering, or solution architecture. ITSM fundamentals: incident vs. service request, prioritization, SLA/OLA concepts, ticket hygiene. ServiceNow proficiency: queue management, routing, and knowledge-base use. Vendor and stakeholder management (Google Cloud Customer Care/TAM, customer executives, HCLTech delivery leadership). Strong experience with Google Cloud Platform services, especially IAM, APIs

Key Responsibilities

• Excellent in providing L1, L2 & L3 support for Gemini Enterprise App related issues.
• Own the full ServiceNow ticket lifecycle including triage, categorization, prioritization, resolution, and closure with no internal L1/L2/L3 handoff beyond this pair.
• Lead the architecture and rollout of Gemini Enterprise App for enterprise search, summarization, assistants, and agent-driven workflows across business functions.
• Design and implement permissions-aware search and retrieval across structured and unstructured enterprise content.
• Configure, manage & support prebuilt connectors for Google and third-party enterprise systems such as Confluence, Jira, SharePoint, ServiceNow, and other knowledge sources.
• Build custom mcp server: Develop & Deploy for non-standard enterprise systems and APIs, including data ingestion, indexing, metadata handling, ACL mapping, and synchronization design.
• Assist, Guide, Create, troubleshoot operationalize no-code / low-code agents using Agent Designer, including single-step and multi-step workflows, orchestration, and recurring task automation.
• Support onboarding and governance of Google-made, third-party, and internally built agents, including custom agents built by internal engineering teams.
• Define and implement identity and access strategies using Google Identity and Workforce Identity Federation, including SSO, group/claim mapping, access-controlled data sources, and user authorization models.
• Partner with IAM and security teams on OIDC/SAML federation, attribute mapping, group-based access, and SCIM-based provisioning where required.
• Establish best practices for prompt design, grounding, response quality, evaluation, and responsible AI adoption across enterprise use cases
• Work with business stakeholders to identify high-value use cases, prioritize rollout waves, and measure adoption, quality, and business impact.
• Create architecture standards, implementation playbooks, and operational runbooks for support and scale.
• Implement, Support GCP Model Armor to protect AI models and agents from adversarial threats, vulnerabilities, and misuse in production environments.
• Establish and refine generative AI evaluation frameworks to assess model performance, accuracy, bias, reliability, and alignment with business KPIs continuously.
• Define and implement comprehensive security strategies: enforce least privileged IAM, monitor agent activities, employ VPC Service Controls, and ensure data encryption and compliance with organizational policies.
• Must be proficient with Terraform, GITHUB Actions & in Python Language.
• Monitor and troubleshoot connectors health, performance, and security incidents using Google Cloud Operations and custom telemetry integrations.
• Document architecture designs, standard operating procedures, troubleshooting guides, and best practices for deploying and managing Gemini Enterprise in production.

Skill Requirements

Required Skills and Expertise

• 8+ years of experience in cloud architecture, enterprise integration, platform engineering, or solution architecture.
• ITSM fundamentals: incident vs. service request, prioritization, SLA/OLA concepts, ticket hygiene.
• ServiceNow proficiency: queue management, routing, and knowledge-base use.
• Vendor and stakeholder management (Google Cloud Customer Care/TAM, customer executives, HCLTech delivery leadership).
• Strong experience with Google Cloud Platform services, especially IAM, APIs, security, and application integration.
• 2+ years of hands-on experience in GenAI / LLM / RAG / enterprise search implementations.
• Strong understanding of identity management integration strategies for cloud-native applications, including Google Workspace, OAuth, and SAML.
• Expertise in deploying and managing AI security tools, especially Google’s Model Armor for protecting generative AI models.
• Experience configuring third-party API connectors and integrating diverse SaaS or on-premises applications with AI agents.
• Familiarity with no-code/low-code automation platforms within AI ecosystems to support rapid agent prototyping and deployment.
• Proficiency in AI/ML evaluation methodologies testing model fairness, accuracy, robustness, and continuous monitoring.
• Strong infrastructure-as-code (Terraform) and CI/CD skills for automated, repeatable deployments.
• Knowledge of cloud security best practices, network segmentation, IAM policies, and compliance frameworks relevant to AI and data-intensive systems.
• Experience with monitoring tools like Cloud Monitoring, Cloud Logging, Prometheus, and custom telemetry to ensure high availability and security posture.
• Excellent documentation, communication, and collaboration skills to work effectively across technical and business stakeholders.

Other Requirements

Qualifications & Certifications:

• Bachelor’s degree in IT/ Engineering/MBA or other management qualification.
• GCP Cloud Architect Certification / GCP Devops / ML Engineer Architect Certification
• Terraform Associate