Senior Backend Engineer

4 days ago

Bengaluru, Karnataka, India Umanist NA Full time ₹ 2,20,00,000 - ₹ 3,80,00,000 per year

Job Title:
Senior Backend Engineer – Azure AI/ML and Data Services Integration 27693

Location:
Chennai, Bangalore, Hyderabad, Pune, Gurgaon

Work Mode:
Hybrid (2 days a week from office)

Experience Required:
7 – 17 Years

Salary Range:
₹22,00,000 – ₹38,00,000 per annum

Notice Period:
Immediate joiners or candidates serving notice (up to 30 days)

Key Responsibilities

  • Design and develop scalable data integration pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake Storage (ADLS).
  • Build, deploy, and maintain AI/ML models using Azure Machine Learning and Azure Cognitive Services.
  • Integrate Azure AI/ML services into existing backend infrastructure for seamless data flow and processing.
  • Collaborate with cross-functional teams to gather and translate requirements into robust solutions.
  • Optimize data workflows and ML models for scalability, performance, and security.
  • Troubleshoot technical issues and ensure consistent, high-quality data processing and model accuracy.

Required Skills & Experience
Backend Development

  • 7–10 years of strong experience with Java, Spring Boot, and microservices architecture.
  • Experience in building secure, scalable backend systems and RESTful APIs.

Azure & Data Services

  • Proficiency with Azure Data Factory, Azure Databricks, Azure Machine Learning, ADLS, and Cognitive Services.
  • Solid understanding of data integration and ETL/ELT workflows.

AI/ML Integration

  • Hands-on experience or working knowledge of machine learning pipelines, including training, deployment, and lifecycle management using Azure tools.

Cloud & Infrastructure

  • Familiarity with Azure cloud infrastructure components: Virtual Machines, Storage, Networking.
  • Experience integrating backend systems with cloud-native services.

Database

  • Working experience with relational and non-relational databases such as PostgreSQL, MySQL, MongoDB, etc.

Nice To Have

  • Azure certifications (e.g., Azure AI Engineer, Azure Data Engineer).
  • Experience designing cloud-native architectures.
  • Exposure to DevOps practices, including CI/CD and Infrastructure as Code (IaC).
  • Understanding of security best practices, such as encryption, role-based access control, and threat management.

Interview Process

  • L1 Technical Screening
  • Client Technical Interview
  • Managerial Round
  • HR Discussion (All interviews will be conducted virtually)

Skills: azure,data,ml,cloud,infrastructure,learning

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