Zensar Technologies - Generative AI Application Developer - LLM / RAG

Position : Generative AI Application Developer

Experience : 7-16 years

Location : Bangalore, Hyderabad, and Pune, India

Notice Period : Early joiners are highly appreciated.

Job Summary :

We are seeking a highly skilled and experienced Generative AI Application Developer to architect, develop, and deploy production-grade AI systems. The ideal candidate will possess deep technical expertise in the end-to-end lifecycle of Generative AI models, with a strong focus on building scalable and robust applications. This role requires a hands-on developer who can translate complex business challenges into innovative solutions using Large Language Models (LLMs) and other generative Responsibilities : Development & Fine-Tuning :

• Design, build, and train Generative AI models and algorithms using deep learning techniques.
• Implement and fine-tune Large Language Models (LLMs) using custom datasets to meet specific business requirements.
• Apply techniques such as Retrieval-Augmented Generation (RAG) and prompt engineering to enhance model performance and reduce Engineering & Preparation :
• Architect and implement data pipelines for the ingestion, preprocessing, and transformation of large datasets.
• Manage and optimize vector databases for efficient semantic search and information Development & Integration :
• Develop robust, scalable applications that integrate Generative AI models using APIs and microservices.
• Build prototypes and demonstrate proof-of-concepts (POCs) to technical and business stakeholders.
• Ensure seamless integration of AI applications with existing enterprise & MLOps :
• Deploy and manage AI models in production environments using MLOps principles.
• Implement CI / CD pipelines for continuous integration and deployment of machine learning code.
• Monitor model performance, latency, and resource utilization & Innovation :
• Stay current with the latest advancements in Generative AI, deep learning, and transformer architectures.
• Evaluate and experiment with new models, frameworks, and tools to drive Skills : :
• Expert-level proficiency in Python.
• Strong experience with software engineering fundamentals, including object-oriented programming, data structures, and Expertise :
• Deep understanding of deep learning frameworks such as PyTorch or TensorFlow.
• Hands-on experience with Generative AI models (e.g., GANs, VAEs) and architectures (e.g., Transformers, diffusion models).
• Proven experience with Large Language Models (LLMs), fine-tuning, RAG, and prompt & Cloud :
• Strong experience with cloud platforms for AI / ML (AWS SageMaker, Azure ML, or GCP Vertex AI).
• Familiarity with MLOps tools like MLflow, Kubeflow, or DVC.
• Experience with containerization technologies like & APIs :
• Experience with vector databases such as Pinecone, ChromaDB, or FAISS.
• Proficient in SQL and knowledge of NoSQL databases.
• Experience with building and consuming RESTful APIs and :
• Hands-on experience with key libraries such as Hugging Face Transformers, LangChain, or Engineering Practices :
• Strong knowledge of version control systems, especially Skills :
• Experience developing SaaS products or consumer-facing applications powered by Generative AI.
• Knowledge of specific cloud-native services like AWS Bedrock, Azure OpenAI Service, or GCP's Vertex AI Model Garden.
• Familiarity with other programming languages such as Java or C++ for high-performance computing.
• Experience with UI / UX frameworks (React, Angular) to build user interfaces for AI applications.
• Contributions to open-source projects in the AI or machine learning community.
• Relevant cloud certifications (AWS Certified Machine Learning Specialty).

(ref : hirist.tech)