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
