Job Description Summary

Job Description

Key Responsibilities

CloudNative & Backend Engineering

• Design develop and maintain scalable microservicesbased applications on a major cloud provider.

• Develop backend services with clean maintainable testable code.

• Ensure availability resiliency scalability performance and observability across services.

• Contribute to system architecture including service decomposition data flows and integration patterns.

• Apply distributed systems best practices including fault tolerance idempotency caching and asynchronous or eventdriven patterns.

• Promote cloudfirst and APIfirst architectural principles.

• Participate in design reviews and provide technical leadership on architecture decisions.

DevOps Platform & Infrastructure as Code

• Implement Infrastructure as Code (IaC) using tools such as Terraform Pulumi or native cloud frameworks.

• Develop and maintain CI/CD pipelines for automated build test security scanning and deployment.

• Use Docker and Kubernetes for containerization and orchestration.

• Build and deploy services using compute storage networking and data services from any major cloud provider.

AI Integration (MCP & Orchestration)

• Implement context providers adapters and orchestration layers that enable reliable interactions between applications and AI models.

• Develop pipelines for prompt engineering context retrieval tool invocation rate limiting and response orchestration.

• Integrate with hosted AI platforms to operationalize AIdriven features.

• Implement guardrails validation monitoring and safety measures to ensure responsible AI usage

• Design and build MCP (Model Context Protocol) servers and supporting components to integrate enterprise systems data sources and workflows with LLMs.

Collaboration & Compliance

• Collaborate effectively with frontend engineers and understand how backend services integrate with TypeScriptbased UI components.

• Work with Data Science Applied AI Platform and Product teams to deliver endtoend features.

• Ensure secure and compliant handling of sensitive healthcare data when applicable.

• Translate business requirements into scalable technical implementations.

• Participate in code reviews quality practices and continuous improvement.

Required Qualifications

• Bachelors or Masters degree in Computer Science Engineering or a related field.

• 6 years of experience building cloudnative applications.

• Handson experience with:

  • Cloud platforms such as AWS Azure or GCP

  • Microservices architecture

  • Docker and Kubernetes

  • CI/CD pipelines

  • Infrastructure as Code using Terraform Pulumi or native cloud frameworks

• Strong understanding of software architecture and distributed systems.

• Working knowledge of (6 years experience):

  • LLMs RAG and Agentic AI concepts

  • AIbased workflow integration including prompting grounding and orchestration

Preferred Qualifications

• Masters degree in Data Science fields

• Experience integrating Generative AI features into production systems.

• Experience in healthcare or medical technology domains.

• Understanding of DICOM standards or imaging workflows.

• Building server components or integration layers including protocolbased services such as MCP servers

Key Competencies

• Strong architectural thinking and systems problemsolving.

• Ability to design and build scalable cloudnative systems with operational excellence.

• Curiosity and adaptability with emerging AI technologies and patterns.

• Excellent debugging and troubleshooting skills across distributed systems.

• Effective communication and collaboration across crossfunctional teams.

Additional Information