Senior Java Developer
Virtusa · New York, NY · 1 wk ago
HybridEngineeringFull-time
Primary Responsibilities
- Lead end to end design and development of Java full stack applications from concept through production
- Develop and integrate AI driven capabilities including vector search, semantic search and intelligent retrieval systems
- Build scalable, secure, and resilient cloud native solutions supporting P1 critical applications handling PII data
- Drive benefit digitization efforts to accelerate delivery timelines for Benefit Answers and Benefit Hub
- Provide onshore support for UAT and Production ensuring timely issue resolution and system stability
Required Skills And Attributes
- 8-12 years of experience in software development with strong Java full stack expertise
- Hands-on experience with Java frontend frameworks, REST API development, and distributed systems
- Experience with cloud platforms
- Working knowledge of AI, ML integration in applications, vector search, semantic search solutions
- Strong understanding of secure coding practices especially in PII sensitive environments
- System performance, reliability, and scalability experience
- Experience supporting UAT and Production environments
Preferred Skills And Attributes
- 10 years of experience with exposure to AI-powered platforms or solutions
- Experience with LLM integrations, embeddings, and vector databases
- AI orchestration frameworks or intelligent agent systems familiarity
- Familiarity with Healthcare Benefits domain, Benefit Answers, Benefit Hub or similar enterprise platforms
- Experience with Observability tools, data pipelines, and real-time processing systems
- Prior experience working in global delivery models
- Domain background in Healthcare Insurance or Benefits platform experience
- Experience working on mission-critical applications
- Exposure to systems managing member data and PII
Essential for Ensuring On Time Delivery of a P1 Critical Application
- AI skills consistent use, maintaining 90% weekly usage of approved AI tools
- Applied productivity use, enhancing coding, documentation, data analysis, and decision-making workflows
- Continuous learning, staying current with evolving AI capabilities and applying them to improve delivery quality and velocity