JD: Java Full Stack Developer
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 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 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
Preferred Experience Domain Background
Healthcare Insurance or Benefits platform experience
Experience working on mission critical applications
Exposure to systems managing member data and PII
The application handles PII data requiring onshore support for compliance
Requires real time UAT and Production support coordination
Essential for ensuring on time delivery of a P1 critical application.
AI Skills
Consistent Use Maintain 90% weekly usage of approved AI tools
Applied Productivity: Use AI tools to enhance coding, documentation, data analysis, and decision-making workflows
Continuous Learning: Stay current with evolving AI capabilities and apply them to improve delivery quality and velocity