Senior Cloud and AI Integration engineer
GE HEALTHCARE
Bengaluru, Karnataka, IndiaSENIOR
Job Description
Software Engineer with expertise in AI integration.
Responsibilities
- Design, develop, and maintain scalable microservices‑based 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 event‑driven patterns.
- Promote cloud‑first and API‑first architectural principles.
- Participate in design reviews and provide technical leadership on architecture decisions.
- 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.
- 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 AI‑driven 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.
- Collaborate effectively with frontend engineers and understand how backend services integrate with TypeScript‑based UI components.
- Work with Data Science, Applied AI, Platform, and Product teams to deliver end‑to‑end 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.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 3+ years of experience building cloud‑native applications.
- Hands‑on 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 (2+ years working experience):
- LLMs, RAG, and Agentic AI concepts
- AI‑based workflow integration including prompting, grounding, and orchestration
Nice to have
- Master’s 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 protocol‑based services such as MCP servers
- Strong architectural thinking and systems problem‑solving.
- Ability to design and build scalable cloud‑native 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 cross‑functional teams.