Key Responsibilities-

AI / Agent Development

- Design and develop AI agents and multi-agent systems for enterprise use cases (workflow automation, copilots, decision systems).
- Build agent orchestration frameworks leveraging LLMs and tool integrations.
- Develop solutions for document processing, summarization, classification, and knowledge retrieval systems.

Application Engineering &

- Platform Integration

- Develop end-to-end AI-enabled applications integrating:

Backend systems

APIs and microservices

Data platforms

- Ensure seamless integration with enterprise systems across claims platforms, document hubs, and workflow engines.

Software Engineering &

- Architecture

- Build and maintain scalable microservices-based architectures using modern software engineering practices.
- Implement robust APIs and reusable frameworks for AI services.
- Ensure high standards in code quality, performance optimization, and maintainability.

Data, DevOps &

- Production Support

- Design and manage data pipelines, storage, and retrieval mechanisms.
- Leverage Azure DevOps and CI/CD pipelines for automated build, release, and deployment.
- Provide production support, monitoring, and continuous improvements for deployed AI solutions.

Technical Skills

Core Engineering Skills

- Programming: Python (mandatory), solid backend development experience
- Database:



SQL (data modeling, querying, performance tuning)
- Architecture: Microservices architecture, RESTful APIs
- Application Engineering: End-to-end solution design (backend + integrations)

AI / ML &

- Automation

- Experience with AI/ML solutions in production environments
- Experience with LLM frameworks (LangChain, Semantic Kernel, or similar)
- Knowledge of prompt engineering, RAG architecture, vector databases
- Hands-on experience with:

AI-driven automation platforms Copilot / Agent-based systems

Document processing or NLP-based applications

Leverage and develop Harness framworks and AI Tools (mandatory)

Platform &

- DevOps

- Azure ecosystem (preferred)
- Azure DevOps (CI/CD pipelines, release management)
- Knowledge of cloud-native application development

Frameworks &

- Engineering Practices

Strong Grounding In

- Software engineering frameworks and patterns
- API-first design
- Scalable and distributed systems

Preferred Skills

- Experience in Disability, Insurance, or Claims domain
- Familiarity with observability tools (Application Insights, monitoring frameworks)
- Exposure to enterprise AI governance, security, and compliance

Experience – 8–12 years of experience in software engineering with focus on AI/ML or platform development

📌 Sr. Software Platform Engineer II (Hyderabad)
🏢 MetLife
📍 Hyderabad