Full Stack Engineer

• Full-Stack - GenAI
• Location:- Bangalore - Whitefield
• Experience:- 5–8 years
• About the Role
• End-to-end developer responsible for building GenAI/AI-powered proof-of- concepts, prototypes, and applications within the innovation POD.
• Will work closely with the Innovation Manager and Data Science/Prompt Engineer to deliver functional solutions rapidly. The role requires someone
• who can independently take an idea from concept to working prototype.
• Key Responsibilities

• Design and develop end-to-end PoC solutions covering both frontend and backend
• Build AI-powered applications, dashboards, and automation tools
• Integrate GenAI/LLM APIs and services into business applications
• Deploy and manage solutions on Microsoft Azure cloud platform
• Collaborate with the Data Science/Prompt Engineer to build AI-driven features
• Ensure code quality, documentation, and reusability of solutions
• Participate in innovation brainstorming and technical feasibility assessments
• Present technical demos and walkthroughs to client stakeholders

Must-Have Skills

• 5–8 years of full-stack development experience
• Strong proficiency in Python
• Strong proficiency in React (frontend)
• Experience with Microsoft Azure stack (Azure App Services, Azure Functions, Azure AI Services)
• Experience integrating REST APIs and working with microservices architecture
• Knowledge of databases (SQL and NoSQL)
• Good communication skills for client-facing interactions

Good to Have

• Experience with Azure OpenAI Service and Azure AI Foundry
• Familiarity with CI/CD pipelines and Azure DevOps
• Curiosity to test latest technologies for both implementing and enhancing work (Codex, GPT, Copilot)

• ● Develop and deploy scalable Generative AI and LLM-based solutions on Azure
• or GCP or AWS
• ● Agentic AI Development: Design, build, and deploy agentic AI systems using
• frameworks such as LangChain, LangGraph, and related libraries. Develop and
• deploy multi-agent systems capable of autonomous decision-making,
• reasoning, planning, and collaboration.
• ● RAG Pipelines: Implement and optimize retrieval-augmented generation (RAG)
• systems, ensuring agents can access and incorporate external knowledge
• sources for grounded, accurate responses.
• ● Integrate AI models with business applications and build scalable APIs (e.g.,
• FastAPI, Flask) and microservices.
• ● Lead the development of enterprise-grade AI platforms integrating LLMs, RAG,
• embeddings, and agentic AI protocols.
• ● Implement and standardize Model Context Protocol (MCP) for consistent
• context management across models and agents.
• Required Skills & Qualifications
• ● Programming: Strong proficiency in Python is mandatory, including OOP
• concepts and best coding practices.
• ● Cloud Expertise: Delivered Gen AI or ML projects in cloud(AWS/GCP/Azure)
• ● AI Frameworks: Familiarity with LLM frameworks and libraries such as Google
• ADK, LangChain, LlamaIndex, or similar frameworks.
• ● AI Techniques: Strong understanding of RAG architectures, prompt engineering,
• model optimization, and performance evaluation methodologies.
• ● Infrastructure: Experience with MLOps practices, CI/CD pipelines,
• containerization (Docker/Kubernetes), and infrastructure automation tools like
• Terraform is a plus.
• If youre interested in this opportunity, please share your updated CV at [HIDDEN TEXT] or WhatsApp it to 8827565832.
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