Senior Principal Consultant - AI Senior Engineer

Ready to shape the future of work
At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges.If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment.Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.Inviting applications for the role of Senior Principal Consultant - AI Senior Engineer!

In this role you&rsquoll be leveraging Azure&rsquos advanced AI capabilities or AWS Advance Ai capability, including Azure Machine Learning , Azure OpenAI, PrompFlow, Azure Cognitive Search, Azure AI Document Intelligence,AWS Sage Maker, AWS Bedrocks to deliver scalable and efficient solutions. You will also ensure seamless integration into enterprise workflows and operationalize models with robust monitoring and optimization.
Responsibilities. AI Orchestration - Design and manage AI Orchestration flow using tools such as: Prompt Flow, Or LangChain Continuously evaluate and refine models to ensure optimal accuracy, latency, and robustness in production.. Document AI and Data Extraction, Build AI-driven workflows for extracting structured and unstructured data fromLearning, receipts, reports, and other documents using Azure AI Document Intelligence, and Azure Cognitive Services.. RAG Systems - Design and implement retrieval-augmented generation (RAG) systems using vector embeddings and LLMs for intelligent and efficient document retrieval Optimize RAG workflows for large datasets and low-latency operations.. Monitoring and Optimization - Implement advanced monitoring systems using Azure Monitor, Application Insights, and Log Analytics to track model performance and system health Continuously evaluate and refine models and workflows to meet enterprise-grade SLAs for performance and reliability.. Collaboration and Documentation - Collaborate with data engineers, software developers, and DevOps teams to deliver robust and scalable AI-driven solutions Document best practices, workflows, and troubleshooting guides for knowledge sharing and scalability.

Qualifications we seek in youMinimum Qualifications. Proven experience with Machine Learning, Azure OpenAI, PrompFlow, Azure Cognitive Search, Azure AI Document Intelligence, AWS Bedrock, SageMaker Proficiency in building and optimizing RAG systems for document retrieval and comparison.. Strong understanding of AI/ML concepts, including natural language processing (NLP), embeddings, model fine-tuning, and evaluation Experience in applying machine learning algorithms and techniques to solve complex problems in real-world applications Familiarity with state-of-the-art LLM architectures and their practical implementation in production environments Expertise in designing and managing Prompt Flow pipelines for task-specific customization of LLM outputs.. Hands-on experience in training LLMs and evaluating their performance using appropriate metrics for accuracy, latency, and robustness Proven ability to iteratively refine models to meet specific business needs and optimize them for production environments.. Knowledge of ethical AI practices and responsible AI frameworks.. Experience with CI/CD pipelines using Azure DevOps or equivalent tools Familiarity with containerized environments managed through Docker and Kubernetes.. Knowledge of Azure Key Vault, Managed Identities, and Azure Active Directory (AAD) for secure authentication.. Experience with PyTorch or TensorFlow.. Proven track record of developing and deploying Azure-based AI solutions for large-scale, enterprise-grade environments.. Strong analytical and problem-solving skills, with a results-driven approach to building scalable and secure systems.Why join Genpact. Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation. Make an impact - Drive change for global enterprises and solve business challenges that matter