CGI - Software Development Engineer - Cloud & Artificial Intelligence

Role Overview : We are seeking a forward-looking Software Development Engineer to design, build, and scale next-generation applications leveraging cloud-native architectures, AI/ML capabilities, and modern engineering practices. The ideal candidate is a strong software engineer with expertise in distributed systems, AWS cloud technologies, platform engineering, and AI-powered application development. This individual will help establish foundational capabilities for AI agents, enable scalable agent orchestration frameworks, and drive adoption of AI-assisted software development practices across the engineering organization. The role requires a passion for innovation and emerging AI technologies. The successful candidate will play a key role in building reusable agentic capabilities, integrating Large Language Models (LLMs), enabling AI-driven workflows, and delivering foundational services that accelerate the development of intelligent applications across the enterprise. Key Responsibilities : - Design, develop, and maintain scalable cloud-based applications using AWS services. - Build and integrate AI/ML-powered features and agents into applications using AWS AI services. - Leverage AWS Kiro and AI-assisted development tools to accelerate software delivery, automate tasks, and improve code quality. - Collaborate with cross-functional teams to define, design, and ship new features. - Implement best practices for cloud architecture, security, and performance. - Automate deployment, monitoring, and management of cloud applications. - Write clean, efficient, and maintainable code and contribute to both front-end and back-end development as a full-stack engineer. - Troubleshoot and resolve issues related to cloud infrastructure and applications. - Mentor and guide junior engineers, fostering a culture of continuous improvement. - Stay up-to-date with the latest AWS technologies and industry trends. Minimum Qualifications: - 3+ years of experience in software development, with a focus on cloud technologies. - Proficiency in AWS services such as EC2, S3, Lambda, RDS, and CloudFormation. - Strong programming skills in languages such as Python, Java, or Node.js. - Experienced in deploying and managing applications using Red Hat OpenShift Service on AWS (ROSA). - Experience with containerization technologies like Docker and Kubernetes. - Familiarity with DevOps practices and tools. - Knowledge of CI/CD pipelines and tools like Jenkins, GitLab, or AWS CodePipeline. - Hands-on experience with AWS cloud services and building distributed systems. - Experience integrating AI/ML capabilities into applications (e.g., personalization, NLP, recommendations). - Familiarity with AWS AI/ML services such as Amazon SageMaker, Bedrock, and AgentCore. - Demonstrated experience using AI-assisted development tools (e.g., GitHub Copilot, Claude, Kiro) to accomplish tasks such as generating and reviewing code, writing and maintaining tests, creating documentation, and debugging. - Understanding of prompt engineering, AI workflows, or model integration patterns. - Experience working with generative AI or LLM-based solutions is highly desirable. - Excellent problem-solving skills and attention to detail. - Strong communication and collaboration skills. - Execute with a Sense of Urgency. - Consistently prioritizes safety and security of self, others, and personal data. - Embraces diverse people, thinking, and styles. Behavioural Competencies: - Demonstrates strong ownership and accountability while fostering a collaborative, solution-oriented team culture. - Communicates with clarity and influence, builds trust, and engages effectively with diverse stakeholders across teams and geographies. - Continuously learns and adapts, embracing new ideas, emerging technologies, and innovative approaches to improve ways of working. - Shows curiosity about business needs and customer priorities, aligning behaviors and decisions to deliver meaningful outcomes. Preferred Qualifications: - Bachelors degree in Computer Science, Information Systems, Engineering, or a related technical field. - AWS Certified Solutions Architect or Developer certification. - Experience with microservices architecture and serverless computing. - Understanding of networking and security principles in cloud environments. - Familiarity with Model Context Protocol (MCP) for connecting AI models to external tools and data sources.