About this role
At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.
Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.
We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status. Generative AI & AI Engineering
• Design, develop, and deploy enterprise Generative AI applications using Azure OpenAI Services. • Build and optimize Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases. • Develop AI-powered chatbots, document Q&A systems, summarization engines, and intelligent automation solutions. • Implement semantic search solutions using vector databases such as FAISS and Azure AI Search. • Engineer prompts and optimize LLM performance for enterprise use cases. • Build AI Agents and agentic workflows using modern orchestration frameworks. • Integrate Vision LLMs for document understanding, image analysis, OCR, and multimodal AI applications. • Develop document processing pipelines using PyMuPDF and OCR technologies. • Implement model evaluation, prompt testing, experimentation, and observability frameworks. • Optimize AI models and services for scalability, latency, reliability, and cost efficiency. Python & Backend Engineering
• Design, develop, and maintain scalable Python applications and services. • Build RESTful APIs and microservices using FastAPI, Flask, and Django. • Write clean, reusable, maintainable, and well-documented code. • Implement multithreaded and asynchronous applications for high-performance workloads. • Integrate applications with databases, cloud services, AI platforms, and third-party APIs. • Troubleshoot production issues and perform root-cause analysis. • Develop automated unit tests, integration tests, and performance tests. • Participate in code reviews and mentor junior developers. • Build secure, reliable, and scalable software architectures. Cloud, DevOps & Deployment
• Deploy AI and backend applications on Azure, AWS, or GCP. • Implement containerized deployments using Docker and Kubernetes. • Build CI/CD pipelines using Azure DevOps, GitHub Actions, or similar tools. • Implement monitoring, logging, alerting, and performance benchmarking. • Ensure compliance with security, governance, and Responsible AI practices. • Collaborate with architects, product managers, data scientists, and engineering teams.
Generative AI
• Large Language Models (LLMs) • Prompt Engineering • Retrieval-Augmented Generation (RAG) • Embeddings • Semantic Search • AI Agents / Agentic Workflows • Function Calling • Context Management • Model Evaluation • Prompt Optimization • LLM Monitoring & Observability AI Platforms & Cloud Services
• Azure OpenAI Service • Azure AI Services • Azure AI Search / Cognitive Search • Azure Storage • Azure Functions Programming & Backend Development
• Python (Advanced) • Object-Oriented Programming (OOP) • Data Structures & Algorithms • FastAPI • Flask • REST API Development • OpenAPI / Swagger • JSON • OAuth2 / JWT Authentication • Async Programming • Multithreading AI Frameworks & Libraries
• LangChain • LlamaIndex • LangGraph • OpenAI SDK • PyMuPDF • FAISS Vector Database • Vision LLMs Databases
• PostgreSQL • Oracle • Redis Messaging & Event Processing
• RabbitMQ • Apache Kafka • Redis Cache DevOps & Infrastructure
• Docker • Kubernetes • Git • GitHub • Azure DevOps • CI/CD Pipelines Evaluation & Observability
• Opik • Evaluation • Experiment Tracking • LLM Monitoring • Performance Benchmarking Document Intelligence
• Azure Document Intelligence • OCR Technologies • Tesseract OCR • PDF Processing • Document Parsing & Extraction
Required Experience
• 5 to 10 years of software development experience with strong Python expertise. • 2 to 3 years of hands-on experience in Generative AI and LLM-based application development. • Strong experience developing scalable REST APIs using FastAPI, Flask, or Django. • Experience designing and implementing enterprise RAG architectures. • Hands-on experience with Azure OpenAI Service and AI solution deployment. • Experience with Vector Databases such as FAISS and Azure AI Search. • Experience integrating Vision LLMs, OCR, and document intelligence solutions. • Experience with relational and NoSQL databases. • Experience building microservices and distributed systems. • Experience deploying applications using Docker and Kubernetes. • Experience implementing CI/CD pipelines and DevOps practices. • Experience with AI observability, evaluation, and monitoring tools. • Strong debugging, performance optimization, and troubleshooting skills. • Experience working in Agile/Scrum delivery environments. Preferred Qualifications
• Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field. • Experience with Agentic AI architectures and multi-agent systems. • Experience in MLOps and AI Governance. • Experience building enterprise knowledge management and document intelligence platforms.