Java Full Stack Developer

We are seeking a hands-on Platform Engineer with strong Full Stack Development, AI Engineering, and Software Architecture skills to design, develop, deploy, and support scalable, secure, and reliable applications., * Design, develop, test, and operate production-grade APIs, backend services, web applications, and developer-facing platforms. Build self-service portals, infrastructure platform catalogs, reusable components, and automation that simplify adoption of approved platform capabilities.

• Develop integrations across application services, databases, messaging platforms, API gateways, and enterprise engineering tools.
• Write maintainable, secure, well-tested code and participate in code reviews, design discussions, troubleshooting, and performance optimization.
• Own capabilities throughout the SDLC, including CI/CD, deployment, rollback, documentation, and operational readiness. AI Engineering and Intelligent Automation
• Build AI agents and AI-assisted workflows for architecture analysis, engineering knowledge discovery, evidence collection, standards validation, and remediation planning.
• Develop retrieval-augmented generation solutions that ground responses in authorized architecture documents, code, configuration, and platform knowledge.
• Integrate agents with enterprise APIs and tools through controlled interfaces, including Model Context Protocol (MCP) where appropriate.
• Implement evaluation frameworks for accuracy, grounded ness, safety, consistency, latency, and cost.
• Engineer production controls for AI systems, including access restrictions, bounded execution, auditability, human approval, and safe fallback behavior.
• Automate architecture-review feedback and remediation tracking within developer workflows.

• Strong hands-on software development experience using Java, Python, C#/.NET, or comparable backend technologies.
• Experience developing user interfaces with React, Angular, TypeScript, or an equivalent modern framework.
• Demonstrated ownership of production applications or platform services, from design through operational support.
• Experience designing APIs, distributed systems, asynchronous integrations, and relational or NoSQL data access.
• Practical experience developing LLM-enabled applications, AI agents, retrieval workflows, or AI-powered automation.
• Experience with containers, Kubernetes or equivalent platforms, CI/CD, and infrastructure/configuration as code.
• Strong understanding of authentication, authorization, secrets management, secure coding, and data protection.
• Ability to diagnose application, database, network, and dependency-related performance or reliability issues.
• Strong collaboration skills and the ability to explain technical decisions and trade-offs to diverse stakeholders.