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), strong 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