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GCP Cloud Integration for HR Assistant

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placeIN home_workRemoto assignmentContrato publicVaga agregada · IN

eventPublicada em 28 de set. de 2026 · verifiedVerificamos em 01 de out. de 2026 que ainda está no ar

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₹ 12.500 – ₹ 37.500 por projeto

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Job Title Freelance GCP Cloud Integration Engineer for Engage Lynk HR Maya Assistant Project Description Engage Lynk is seeking an experienced Cloud Integration Engineer to deploy, secure, integrate, and test Maya, our HR workflow and policy-assistance platform. The backend and algorithm architecture are prepared. The selected freelancer will productionize the system on Google Cloud Platform, integrate the Gemini API, configure secure authentication, connect the website interface, and verify the complete deployment. This is a hands-on implementation project, not a consultation-only assignment. Roles and Responsibilities Review Maya’s existing Node.js backend, frontend, algorithm, and policy corpus. Deploy the application to Google Cloud Run. Configure Cloud Build and Artifact Registry. Store Gemini credentials securely in Google Secret Manager. Configure IAM roles using least-privilege access. Create or configure a dedicated service account. Implement OIDC or Workload Identity Federation where required. Connect the engagelynk.com interface to the Cloud Run backend. Configure HTTPS endpoints, CORS, security headers, and rate limiting. Implement and test /health and /api/ask endpoints. Integrate policy-grounded retrieval and source citations. Configure webhook authentication, signatures, replay protection, and idempotency. Protect employee and confidential HR information. Configure Cloud Logging, monitoring, alerts, and error reporting. Troubleshoot deployment, permissions, API, dependency, and networking issues. Conduct security, functional, load, and failure-recovery testing. Produce deployment documentation and a rollback procedure. Transfer complete administrative ownership to Engage Lynk. Required Technical Skills Google Cloud Platform Cloud Run Cloud Build Artifact Registry Secret Manager Google IAM and service accounts Node.js and Express.js REST API and webhook integration Gemini API or similar LLM API integration OAuth 2.0, OIDC and Workload Identity Federation JSON and YAML configuration Git and CI/CD Cloud Logging and monitoring Application security and privacy controls Linux, Bash and Google Cloud Shell Preferred Experience AI assistant or RAG application deployment Policy-grounded response systems HR technology or sensitive-data applications Prompt-injection and data-exfiltration controls API Gateway, Cloud Armor or equivalent controls Infrastructure as Code using Terraform Google Cloud Professional certification Expected Deliverables Maya deployed successfully on Google Cloud Run. Public Cloud Run URL connected to the Engage Lynk website. Gemini API connected through Secret Manager. Working health and chat endpoints. Policy corpus and algorithm integrated correctly. IAM and authentication controls configured. Logging, monitoring and alerts activated. Security and functional test report. Final source code and configuration package. Deployment, maintenance and rollback documentation. Knowledge-transfer session with Engage Lynk. No vendor lock-in or freelancer-controlled credentials. Acceptance Criteria The project will be accepted when: /health reports Maya as operational. The provider status confirms Gemini connectivity. General HR policy questions return valid responses. Sensitive requests are blocked or routed for human review. Secrets are absent from source code and logs. Unauthorized origins and requests are rejected. Engage Lynk has full ownership of the GCP resources, code and credentials. Deployment can be reproduced using the supplied documentation. Freelancer Application Requirements Applicants should provide: Relevant GCP and Cloud Run projects Experience deploying Node.js or AI applications Experience with IAM, OIDC and Secret Manager Proposed implementation approach Estimated delivery schedule Fixed-price or hourly quotation Availability for testing and knowledge transfer Screening Questions Have you deployed a Node.js AI application on Google Cloud Run? How would you manage Gemini API credentials securely? How would you prevent unauthorized access to internal HR data? Have you implemented OIDC or Workload Identity Federation? How would you secure incoming and outgoing webhooks? What tests would you complete before production release? Can you provide complete deployment and rollback documentation? Important: Do not request Gemini keys, Google passwords, service-account private keys, or other credentials through Freelancer chat. Access will be granted through controlled GCP IAM permissions.

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