AI Specialist - Innovation Engineer

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).

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Job Title: AI Specialist - Innovation Engineer
Position Id : J0526-0532
Experience: 6+
Shift: 1:00PM TO 10:00PM (5 days ODC)
Main Location: India ( Hyderabad)
Employment Type: Full Time
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Education Qualification:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field with relevant industry experience.
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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.
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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.

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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
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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____

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 s…