AI & Analytics Engineer GenAI & Analytics - CGI

Founded in 1976, CGI is among the largest independent IT and business consulting services firms in the world. With 94,000 consultants and professionals across the globe, CGI delivers an end-to-end portfolio of capabilities, from strategic IT and business consulting to systems integration, managed IT and business process services and intellectual property solutions. CGI works with clients through a local relationship model complemented by a global delivery network that helps clients digitally transform their organizations and accelerate results. CGI Fiscal 2024 reported revenue is CA$14.68 billion and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB). Learn more at cgi.com. Job Title: AI & Analytics Engineer Position ID: J0626-2101 Software Engineer / Senior Software Engineer Experience: 4–7 Years Category: Artificial Intelligence Engineering Shift: General Main Location: Pune , India Employment Type: Full Time Education Qualification: Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field, or higher, with a minimum of 4 years of relevant experience. ________ Position Description: We are looking for an experienced AI Engineer with 4 to 7 years of professional experience to join our team. The ideal candidate is passionate about designing, building, and deploying scalable Artificial Intelligence and Machine Learning solutions, with a specialized focus on Natural Language Processing (NLP) and Generative AI. In this role, you will work on state-of-the-art MLOps practices, construct intelligent AI agents, and develop self-service analytics solutions. You will collaborate closely with product managers, data engineers, backend developers, and business stakeholders to deliver high-quality AI-powered solutions deployed across hybrid and native cloud environments.

Your future duties and responsibilities

• Design and develop AI and Machine Learning models with a strong emphasis on Natural Language Processing (NLP) and Generative AI technologies.
• Explore, implement, train, fine-tune, and evaluate AI models using industry-standard tools and frameworks.
• Manage MLOps lifecycles, including model training, deployment, monitoring, and optimization using Python and Project Jupyter toolsets.
• Develop self-service analytics solutions utilizing Python and SQL to support data-driven decision-making.
• Build and deploy intelligent AI agents and agentic workflows, including Model Context Protocol (MCP) server-based solutions.
• Apply software engineering best practices to ensure code quality, maintainability, testing, and documentation standards.
• Deploy and manage workloads in hybrid and cloud-native environments, with a focus on Red Hat OpenShift and Google Cloud Platform (GCP).
• Enhance data-driven solutions by supporting data ingestion, transformation, reporting, and machine learning capabilities.