AI Full Stack Developer (Gen AI, React & Microservices)

Role Overview

We are seeking a Senior AI Full Stack Engineer with strong expertise in Generative AI, modern frontend frameworks, and scalable backend systems. This role focuses on building production-grade AI-powered applications across Industrial AI, Healthcare AI, and Manufacturing AI domains.

You will design, develop, and deploy full stack solutions integrating large language models and machine learning systems into real-world applications that deliver measurable business impact.

Key Responsibilities

• Design and develop end-to-end full stack applications integrating Generative AI capabilities
• Build responsive and high-performance user interfaces using React.js
• Architect and develop scalable microservices and RESTful APIs
• Implement Retrieval Augmented Generation (RAG) pipelines, embeddings, and vector search solutions
• Develop and optimize Agentic AI workflows involving multi-step reasoning and tool integration
• Fine-tune and optimize large language models for domain-specific use cases
• Work with structured and unstructured data using Python libraries such as Pandas and NumPy
• Develop machine learning models including predictive analytics and computer vision models using OpenCV and CNNs
• Implement MLOps practices for model deployment, monitoring, and lifecycle management
• Deploy applications on cloud platforms such as Microsoft Azure, AWS, or GCP
• Build and maintain CI/CD pipelines using GitHub Actions, Jenkins, or Azure DevOps
• Ensure application scalability, performance, security, and compliance
• Participate in agile ceremonies, design discussions, and code reviews
• Mentor junior developers and contribute to engineering best practices
• Collaborate with data scientists, product managers, and UX teams to deliver AI-driven solutions

Required Skills and Qualifications

• Strong programming experience in Python, .NET, or Java
• Proficiency in React.js including modern hooks and performance optimization
• Experience designing and building microservices-based architectures
• Hands-on experience with Generative AI technologies including LLMs, RAG, embeddings, and prompt engineering
• Experience building production-grade AI applications
• Strong understanding of machine learning concepts including NLP, predictive modeling, and computer vision
• Experience with data processing libraries such as Pandas and NumPy
• Experience with vector databases such as Pinecone, FAISS, ChromaDB, or Cosmos DB
• Experience with relational databases such as PostgreSQL or MySQL
• Familiarity with object storage systems such as Azure Blob Storage or MinIO
• Experience working with cloud platforms such as Azure (preferred), AWS, or GCP
• Experience with DevOps tools such as GitHub, Azure DevOps, or Jenkins
• Familiarity with code quality and security tools such as SonarQube and Veracode

Good to Have

• Experience in Industrial AI, Healthcare AI, or Manufacturing AI domains
• Understanding of LLM performance tuning, latency optimization, and cost control
• Knowledge of rate limiting, API governance, and distributed system design
• Familiarity with data compliance standards such as GDPR, HIPAA, SOC2, or ISO
• Experience with modern developer tools such as Cursor, Claude Code, or Miro
• Strong understanding of design patterns and system architecture principles

What We Offer

• Opportunity to build production-grade AI systems with real-world impact
• Exposure to cutting-edge technologies in Generative AI and machine learning
• Collaborative environment with cross-functional teams including AI engineers, data scientists, and product teams
• Opportunities for career growth into technical leadership roles
• Flexible work environment
• Work closely with Top notch product or customization for fortune 100 clients

Preferred Candidate Profile

• 5- 12 years of overall Experience with building and deploying end-to-end Generative AI applications in most recent 3 years.
• Ability to balance trade-offs between performance, scalability, and cost
• Strong problem-solving and system design skills
• Ability to translate complex AI concepts into user-friendly applications
• Out of the box thinker to "get things done" with help of best available AI tools, but not compromising on Engineering best practices.