Packaged/SaaS Application Engineer

5 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Project Role :

Packaged/SaaS Application Engineer

Project Role Description :

Configure and support packaged or SaaS applications to adapt features, manage releases, and ensure system stability. Use standard tools, APIs, and low-code platforms to align solutions with business needs while preserving compatibility and performance.

Must have skills :

Microsoft Azure AI foundry

Good to have skills :

NA

Minimum 5 Year(s) Of Experience Is Required

Educational Qualification :

15 years full time educationSummary: As a Packaged/SaaS Application Engineer, you will configure and support packaged or Software as a Service applications to adapt features, manage releases, and ensure system stability. Your typical day will involve utilizing standard tools, APIs, and low-code platforms to align solutions with business needs while maintaining compatibility and performance across various systems. You will engage with cross-functional teams to understand requirements and implement effective solutions that enhance user experience and operational efficiency. Roles & Responsibilities: - Expected to be an SME. - Collaborate and manage the team to perform. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Provide solutions to problems for their immediate team and across multiple teams. - Facilitate knowledge sharing sessions to enhance team capabilities. - Monitor application performance and implement improvements as necessary. Professional & Technical Skills: Azure Cloud Engineering : o AI Foundry: integrate and deploy models via Azure-hosted LLM services. o Service Bus: message-based orchestration for triggering Databricks jobs and managing data flow. o Authentication: managed identities, service principals, RBAC. o Networking & Security: Azure subnets, NSG/NCC rules, private endpoint configuration, secure ingress/egress patterns. Databricks Platform : o Notebook development: modular, reusable notebooks with parameterization and error handling. o Jobs: configure, schedule, monitor; handle failures and retries. o Model Serving: Databricks endpoints, serverless vs all-purpose clusters, secure access via service principals/managed identities. o Integration: Databricks service connections deployed via Azure. General AI Knowledge : o MLOps & model lifecycle management (artifacts, versioning). o Monitoring and observability best practices. o Real-time vs batch model serving. Additional Information: - The candidate should have minimum 5 years of experience in Azure Cloud Engineering/Databricks Platform/General AI Knowledge. - A 15 years full time education is required.

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