EY EY - GDS Consulting AI Enabled Automation Full Stack Senior- E 

India, Uttar Pradesh 

110946851

Key Responsibilities:

• Lead the end-to-end design, development, and deployment of scalable and robust AI-powered applications, from frontend interfaces to backend services.
• Architect and implement Generative AI solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and agentic frameworks.
• Develop and integrate complex conversational AI systems and chatbots, focusing on natural language understanding and generation.
• Design and implement robust backend APIs and data pipelines using Python and Node.js, ensuring high performance and scalability for AI workloads.
• Develop interactive, intuitive, and user-friendly front-end interfaces using either ReactJS or Angular, ensuring seamless user experiences with AI capabilities.
• Collaborate with AI Researchers, Data Scientists, and other stakeholders to translate complex AI models and research into deployable, production-ready applications.
• Write clean, maintainable, and high-quality code, conducting thorough testing, debugging, and refinement to ensure optimal performance and reliability.
• Stay abreast of the latest advancements and trends in Generative AI, Conversational AI, and full-stack technologies, applying them to enhance our product offerings.
• Provide technical leadership, mentorship, and conduct comprehensive code reviews for junior developers, fostering a culture of technical excellence.

Qualifications:

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field.
• Minimum 6-9 years of progressive experience in full-stack software development, with at least 3-4 years specifically on AI-driven projects (Conversational AI and Generative AI).
• Demonstrable experience building and deploying Generative AI solutions (e.g., RAG pipelines, fine-tuning LLMs, prompt engineering, using frameworks like LangChain or LlamaIndex).
• Strong practical experience with conversational AI platforms and developing chatbots.
• Advanced proficiency in Python for AI/ML development and backend services.
• Advanced proficiency in JavaScript/TypeScript, with strong, demonstrable experience with either ReactJS or Angular, and server-side programming with Node.js.
• Proven experience with cloud platforms, preferably Azure (e.g., Azure OpenAI, Azure ML, Azure AI Search, Azure Functions, Azure Web Apps).
• Solid understanding and experience with database technologies, including both relational databases (e.g., SQL Server, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cosmos DB, Vector Databases).
• Experience with API design and development (RESTful APIs).
• Deep understanding of NLP, ML algorithms, and deep learning techniques relevant to AI applications.
• Familiarity with data preprocessing, feature engineering, and MLOps practices.
• Strong problem-solving, analytical, and architectural design skills.
• Excellent communication, collaboration, and presentation skills for effective interaction with technical and non-technical teams.
• Experience with Agile development methodologies and proficiency with version control systems (e.g., Git).
• A strong portfolio demonstrating successful full-stack projects involving Conversational AI and/or Generative AI is highly desirable.

Skills:

• Programming Languages: Python (advanced), JavaScript (advanced), TypeScript (required for Angular).
• Frontend Frameworks: Strong proficiency in either ReactJS or Angular.
• Backend Technologies: Node.js (strong proficiency), FastAPI/Flask/Django (Python frameworks).
• Cloud Platforms: Azure (preferred: Azure OpenAI, Azure ML, Azure Functions, Azure App Services, Azure Blob Storage, Cosmos DB).

AI/ML Concepts & Frameworks:

• Generative AI: LLMs, Transformers, Prompt Engineering, Retrieval-Augmented Generation (RAG).
• Conversational AI: NLU, NLG, Intent Recognition, Entity Extraction.
• Libraries/Frameworks: LangChain, LlamaIndex, Hugging Face, TensorFlow, PyTorch.
• Databases: Relational (SQL Server, PostgreSQL), NoSQL (MongoDB, Cosmos DB), Vector Databases (e.g., Pinecone, Azure AI Search/Cognitive Search for vector capabilities).
• API Development: RESTful APIs, Web Services.
• Data Engineering: Data pipelines, ETL/ELT concepts for AI data.
• DevOps & MLOps: CI/CD pipelines, Git, Docker, Kubernetes (familiarity with deployment of AI models).
• Soft Skills: Leadership, problem-solving, analytical thinking, communication, collaboration, adaptability.

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