Custom Software Engineer

Overview

Custom Software Engineer

Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

Must have skills : Java Full Stack Development

Good to have skills : NA

Minimum 12 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Role Summary

Design and deliver enterprise-grade, full-stack solutions leveraging AgentAI tools for accelerated development. Act as a bridge between traditional engineering teams and AI-native specialists, enabling productivity uplift and scalability without deep ML model training or MLOps ownership.

Key Responsibilities

Solution Architecture

• Define end-to-end architecture for full-stack enterprise applications integrating AgentAI copilots, pre-built AI services, and APIs.
• Ensure compliance with SDLC, security, and performance standards while embedding AI-assisted workflows.
  
  

AI Integration

• Use AgentAI tools and LLM-based copilots for coding, testing, debugging, documentation, and design acceleration.
• Incorporate AI services (e.g., RAG-based retrieval, conversational APIs) into enterprise systems.
  
  

Full-Stack Design

• Architect scalable front-end and back-end solutions using modern frameworks and cloud-native patterns.
• Optimize API design, data flows, and UI/UX for AI-assisted features.
  
  

Collaboration

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

Governance & Quality

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

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)

• Java (Spring Boot) – microservices, API integration
• .NET (C#) – enterprise application frameworks
• Python – scripting, automation, AI API integration
  
  

• React / Angular / Vue.js – responsive UI development
• TypeScript / JavaScript – modern front-end engineering
  
  

Additional: SQL/NoSQL, REST/GraphQL APIs, cloud-native skills (Azure/AWS/GCP), containerization (Docker/Kubernetes), CI/CD pipelines.

Additional Information

• The candidate should have minimum 12 years of experience in Java Full Stack Development.
• A 15 years full time education is required.