Sr. Software Platform Engineer II

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