Senior Software Engineer - AI Engineer

Position Description: Founded in , CGI is among the largest independent IT and business consulting services firms in the world. With 94, 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 reported revenue is CA$14.68 billion and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB). Learn more at . Job Title: Senior Software Engineer - AI Engineer Position: Senior AI Engineer Experience: 4 - 6 Years Category: Senior Software Development/ Engineering Shift: General Shift Main location: India, Pune Position ID: J- Employment Type: Full Time Education Qualification: Bachelor's degree in Computer Science or related field or higher with minimum 3 years of relevant experience. #LI-MP14 Your future duties and responsibilities: We are looking for a highly technical AI Engineer to lead the development and deployment of our Generative AI initiatives.

You will be responsible for the end-to-end lifecycle of AI products—from the underlying mathematics of transformer architectures to the cloud-native deployment on Google Cloud Platform (GCP). The ideal candidate bridges the gap between deep academic research (Mathematics and Information Theory) and practical engineering (Fine-tuning, RAG, and MLOps). Core Responsibilities Model Architecture & Development Generative Modeling: Design and implement solutions utilizing Transformers, Diffusion Models, and VAEs.

You will determine when to use decoder-only vs. encoder-decoder architectures based on the use case. LLM Engineering: Optimize Large Language Models through Fine-tuning (LoRA, QLoRA), Prompt Engineering, and Retrieval-Augmented Generation (RAG) to reduce hallucination and improve domain specificity. Algorithmic Optimization: Apply foundations in Linear Algebra and Information Theory to optimize model weights, loss functions, and inference latency.

GCP Ecosystem & AI Infrastructure Vertex AI Orchestration: Manage the full ML lifecycle using Vertex AI Pipelines, Training, and Prediction. Utilize Model Garden for model selection and GenAI Studio for rapid prototyping. Cloud Native Deployment: Containerize models for deployment on GKE (Google Kubernetes Engine) or Cloud Run, ensuring high availability and scalable inference.

Data & Monitoring: Integrate with BigQuery for data retrieval and use Cloud Logging/Monitoring to track model drift and performance in production. Required qualifications to be successful in this role: Good to have : Expert Python: Mastery of the AI stack, including scripting, complex data manipulation, and high-performance model implementation. Mathematical Rigor: Strong command of Calculus, Probability, and Statistics for model evaluation and custom optimization.

GenAI Expertise: Deep understanding of PEFT (Parameter-Efficient Fine-Tuning) and the inner workings of Attention mechanisms. Cloud Engineering: Hands-on experience with GCP IAM, Cloud Functions, and GCS in the context of AI workflows. Good to have : Deep Learning Frameworks: Proficiency in PyTorch or TensorFlow.

Computer Vision & NLP: Experience with CNN architectures for image processing and BERT-based models for advanced NER or Sentiment Analysis. Reinforcement Learning: Familiarity with RL concepts for model alignment (e.g., RLHF). MLOps: Experience building automated CI/CD pipelines specifically for machine learning models.

The Technical Bar: We are looking for an engineer who understands why a model is behaving a certain way at the mathematical level, not just how to call an API. Skills: Agentic AI Agentic RAG AI Data Modeling Cloud Data Platform Design Python (Anaconda) AI/ML TensorFlow