Full-Time
GenAI Developer
Updated on 9/7/2026
Zensar
Digital transformation services
No salary listed
India
In Person
 Software Engineering (1) |
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- Strong Python expertise.
- Advanced proficiency in Python.
- Knowledge of large language models, prompt engineering, Retrieval-Augmented Generation, embeddings, semantic search, AI agents, function calling, context management, and model evaluation.
- Experience with Azure OpenAI Service, Azure AI Services, Azure Storage, LangChain, LlamaIndex, PyMuPDF, FAISS Vector Database, Vision LLMs, OpenAI SDK, Visual Studio Code, PyCharm, Git, GitHub or Azure DevOps, Docker, Opik, prompt evaluation, LLM monitoring, experiment tracking, and performance benchmarking.
- Five to ten years of software development experience.
- Two to four years of hands-on experience in Generative AI and LLM-based application development.
- Experience implementing enterprise Retrieval-Augmented Generation architectures.
- Strong experience with Azure OpenAI.
- Experience integrating Vision LLMs for document and image processing.
- Hands-on experience with vector databases such as FAISS.
- Experience building production-ready AI APIs using FastAPI or Flask.
- Experience processing large PDF and document repositories using PyMuPDF.
- Experience with AI evaluation and observability tools such as Opik.
- Experience deploying AI applications in cloud environments.
- Design, develop, and deploy enterprise Generative AI applications using Azure OpenAI Services.
- Build Retrieval-Augmented Generation pipelines using embeddings and vector databases.
- Develop scalable REST APIs using FastAPI and Flask.
- Integrate Vision LLMs for image, document, and multimodal understanding.
- Build document processing pipelines using PyMuPDF for PDF extraction, parsing, and preprocessing.
- Implement semantic search using the FAISS Vector Database.
- Engineer prompts and optimize LLM responses for enterprise use cases.
- Develop AI-powered chatbots, document question-answering, summarization, and intelligent automation solutions.
- Optimize AI models for latency, scalability, and cost efficiency.
- Integrate AI solutions with enterprise applications and cloud services.
- Implement monitoring, evaluation, and experimentation frameworks using Opik or similar LLM observability tools.
- Collaborate with product managers, architects, data scientists, and software engineers to deliver AI solutions.
- Ensure AI applications follow security, governance, and responsible AI best practices.
- Experience with Azure Cognitive Search, Azure Functions, Transformers, LangGraph, AutoGen or CrewAI, Azure AI Search, Cosmos DB, PostgreSQL, Redis, Kubernetes, MLflow, Hugging Face, optical character recognition using Azure Document Intelligence or Tesseract, continuous integration and continuous delivery pipelines, and MLOps.
Zensar is a global technology services company focused on enterprise digital transformation. The company provides application modernization, artificial intelligence, cloud, cybersecurity, data, engineering, experience, and managed services. It serves enterprises, public organizations, technology leaders, and business teams across multiple industries. Its operating model centers on consulting and delivery teams organized around client programs, industry practices, technology partnerships, and global operations. Teams work across software, cloud, AI, data, cybersecurity, consulting, quality engineering, and client delivery. This structure supports consistent delivery across the organization.
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