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Principal Software Engineer

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Onsite

Principal Software Engineer

Providence India

Principal Software Engineer

Skills

SQL QueriesPythonMachine LearningAIAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Onsite

Published on:

23 August 2026

What they need


How is this team contributing to vision of Providence? Our team is responsible for providing reliable and resilient network connectivity to our hospitals which makes lives of our caregivers easy, contributing to our vision “Health for a better world”.

What will you be responsible for?

  • Design, build, and maintain secure, scalable, cloud-native full-stack applications, APIs, integrations, and AI-enabled platforms.
  • Automate CI/CD, DevOps, and MLOps workflows to improve reliability, reproducibility, and speed of delivery.
  • Drive architecture, design reviews, engineering standards, security, observability, and operational excellence across platforms.
  • Partner with product, architecture, data, platform, and operations teams to deliver high-quality business outcomes.
  • Mentor engineers and promote continuous improvement, automation-first thinking, and strong software engineering practices.

What would your day look like? On a typical day, you will design and deliver full-stack features, backend services, APIs, cloud-native components, and AI/ML integrations while improving platform reliability, debugging production issues, and collaborating across engineering, product, architecture, and operations teams.

Who are we looking for?

  • B.Tech. in Computer Science or related field with 10+ years of professional software engineering experience and strong full-stack development background.
  • Strong programming skills in Python and .NET, with experience building scalable cloud-native services and AI-enabled capabilities.
  • Solid understanding of CI/CD, DevOps, Infrastructure-as-Code, APIs, distributed systems, SQL, data modeling, and production reliability practices.
  • Hands-on exposure to AI/ML lifecycle, MLOps, model deployment, observability, RAG, prompt engineering, or domain-specific AI solutions.
  • Strong debugging, problem-solving, communication, collaboration, stakeholder management, and ability to work effectively in Agile/Scrum environments using Azure DevOps and Git.

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