Senior Software Engineer - Innovation Engineer
CGI
Job Description
Position Description:
We are seeking a highly skilled Senior / Lead Engineer to design and build scalable cloud-native platforms and AI-driven solutions. This role involves architecting distributed systems, developing microservices-based applications, and delivering AI/ML and Generative AI solutions in production environments.
The ideal candidate will lead cloud architecture initiatives, drive strong DevOps and MLOps practices, and collaborate across teams to deliver secure, scalable, and high-performance enterprise-grade applications.
Must-Have Skills:
Strong experience with cloud platforms (AWS / GCP / Azure)
Expertise in microservices architecture and distributed systems
Hands-on experience with Docker and Kubernetes
Experience with CI/CD pipelines and DevOps practices
Experience building AI/ML or Generative AI solutions (LLMs, RAG pipelines, vector databases)
Strong knowledge of API development and integration
Experience implementing MLOps and model lifecycle management
Experience with system monitoring, logging, and observability tools
Good-to-Have Skills:
Knowledge of 12-factor application design principles
Experience with blue-green or canary deployment strategies
Experience with cloud cost optimization and performance tuning
Exposure to enterprise security and compliance standards
Experience mentoring teams and guiding engineering best practices.
Your future duties and responsibilities:
Responsibilities:
• Lead end-to-end design and development of scalable cloud-native products from ideation, PoC, pilot to production rollout.
• Architect and implement distributed systems using microservices, APIs, Docker containers, Kubernetes, and CI/CD pipelines.
• Build, deploy, and optimize AI/ML and Generative AI solutions, including LLM-based applications, RAG pipelines, and vector databases.
• Implement robust MLOps practices including model lifecycle management, versioning, monitoring, and continuous improvement.
• Design highly available, resilient systems following 12-factor application principles with autoscaling and cost optimization.
• Own and manage cloud architecture across AWS, GCP, or Azure ensuring security, compliance, and performance.
• Implement observability for logging, monitoring, alerting, and performance tuning.
• Define and execute deployment strategies such as blue-green and canary releases for zero-downtime deployment.
• Collaborate with product, business, and engineering teams to translate requirements into scalable technical solutions.
• Mentor junior engineers and promote engineering best practices across teams.
Required qualifications to be successful in this role:
Must-Have Skills:
Strong experience with cloud platforms (AWS / GCP / Azure)
Expertise in microservices architecture and distributed systems
Hands-on experience with Docker and Kubernetes
Experience with CI/CD pipelines and DevOps practices
Experience building AI/ML or Generative AI solutions (LLMs, RAG pipelines, vector databases)
Strong knowledge of API development and integration
Experience implementing MLOps and model lifecycle management
Experience with system monitoring, logging, and observability tools
Good-to-Have Skills:
Knowledge of 12-factor application design principles
Experience with blue-green or canary deployment strategies
Experience with cloud cost optimization and performance tuning
Exposure to enterprise security and compliance standards
Experience mentoring teams and guiding engineering best practices.
Skills: