Forward Deployed Engineer

Project Role : Forward Deployed Engineer

Project Role Description : Organize the deployment of AI workflows and architectures across diverse AI and technology platforms. Facilitate solution design across enterprise technology stack to integrate into the ecosystem of AI models and multi provider platforms.

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

Overview:

Role Summary

AI POWERED TECH TALENT

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.AI Powered Tech Talent

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.
  
  

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):

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

Frontend:

• 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.