Java Fullstack

Key Responsibilities

Solution Architecture

o Define end-to-end architecture for full-stack enterprise applications integrating AgentAI copilots, pre-built AI services, and APIs.

o Ensure compliance with SDLC, security, and performance standards while embedding AI-assisted workflows.

AI Integration

o Use AgentAI tools and LLM-based copilots for coding, testing, debugging, documentation, and design acceleration.

o Incorporate AI services (e.g., RAG-based retrieval, conversational APIs) into enterprise systems.

Full-Stack Design

o Architect scalable front-end and back-end solutions using modern frameworks and cloud-native patterns.

o Optimize API design, data flows, and UI/UX for AI-assisted features.

Collaboration

o Act as a liaison between traditional engineering teams and AI-native squads drive adoption of AI-assisted development practices.

Governance & Quality

o Maintain architectural integrity, scalability, and reliability enforce responsible AI usage and guardrails.

Must-Have Qualifications

Solid foundation in enterprise engineering, SDLC, and domain/industry workflows.

Demonstrated capability in using copilots and LLM tools for software development tasks.

Practical understanding of AI concepts like RAG and limitations of LLMs.

Ability to deliver faster, higher-quality outcomes by combining human judgment with AI-assisted productivity.

Does not train models or design ML architectures focuses on integration and productivity uplift.

Programming & Full-Stack Skills

Backend (Any 1 or more):

o Java (Spring Boot) microservices, API integration

o .NET (C#) enterprise application frameworks

o Python scripting, automation, AI API integration

Frontend:

o React / Angular / Vue.js responsive UI development

o TypeScript / JavaScript modern front-end engineering