CGI is hiring a Mid-Level Full-Stack AI Engineer to lead end-to-end delivery of scalable, production-ready AI solutions.

Lead design, development, and deployment of end-to-end AI-powered applications including backend services, APIs, data pipelines, model integrations, and user-facing interfaces
Architect, build, and maintain scalable, secure, high-performance backend services using Python; develop responsive frontend applications using Angular
Design and implement AI capabilities including generative AI, LLMs, NLP, document classification, OCR, and conversational AI
Own machine learning efforts across inference, training, fine-tuning, and optimization to support reliable production performance
Develop and optimize RESTful APIs, system integrations, and database solutions for interoperability, performance, and scalable AI platform components
Implement and maintain CI/CD pipelines and containerized deployments using Docker, Kubernetes, and cloud technologies
Collaborate with product managers, data scientists, UI/UX designers, and engineering teams to translate business requirements into technical designs and AI-driven features
Drive client-focused AI use cases using CGI’s AI Platform, from solution design through production deployment
Monitor, troubleshoot, and optimize production systems to ensure availability, security, reliability, performance, and operational efficiency
Mentor junior engineers; participate in architecture and design reviews; provide technical guidance and promote software engineering best practices

Bachelor’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related technical discipline, or equivalent practical experience
2+ years of professional full-stack development experience with strong Python backend skills and Angular frontend skills
2+ years hands-on experience building AI-powered products involving generative AI, NLP, document classification, chatbots, OCR, or related intelligent automation technologies
Demonstrated experience with machine learning concepts, LLM inference, model integration, and deployment of AI-enabled applications
Strong experience designing and developing RESTful APIs and applying system design and architecture principles for distributed components
Hands-on experience with Docker, Kubernetes, and container orchestration concepts, including production deployment and management
Proficiency with relational and non-relational databases, including design, querying, and performance optimization
Experience with cloud platforms such as Microsoft Azure or Google Cloud Platform (GCP) to develop, deploy, manage, and scale AI applications
Knowledge of secure software development practices, data privacy regulations, compliance requirements, and responsible AI principles
Strong analytical, troubleshooting, communication, and collaboration skills, including ownership of technical deliverables and ability to guide junior team members

Python, Angular
Machine learning, generative AI, large language model (LLM), NLP
Document classification, optical character recognition (OCR), conversational AI
RESTful APIs, CI/CD, Docker, Kubernetes
Relational databases, non-relational databases
Microsoft Azure, Google Cloud Platform (GCP)
LangChain, Hugging Face
Retrieval-augmented generation (RAG), vector databases, embeddings, prompt engineering
AI agent architectures, MLOps
GitHub Actions, Azure DevOps
Microsoft Azure AI services, Google Cloud AI services

Experience building production-grade applications using LLM frameworks, orchestration libraries, or AI development tools such as LangChain, Hugging Face, or similar
Hands-on experience implementing retrieval-augmented generation (RAG), vector databases, embeddings, prompt engineering, or AI agent architectures
Experience with model fine-tuning, model evaluation, MLOps practices, and monitoring AI models in production
Experience building and maintaining automated CI/CD pipelines, testing frameworks, and deployment workflows using GitHub Actions, Azure DevOps, or similar tools
Experience designing and deploying AI-powered solutions using Microsoft Azure AI services, Google Cloud AI services, or related cloud-native AI technologies
Demonstrated experience leading technical feature development, mentoring engineers, contributing to architectural decisions, and delivering customer-focused AI solutions

Knoxville, TN (onsite)
May be based in any CGI office in the United States, with Knoxville, TN as the preferred location

USD 79,600 - 109,500 per yearly
CGI provides a reasonable estimate of compensation range; actual compensation depends on factors including skill set, level, experience, relevant training, and licensure and certifications

Competitive compensation
Comprehensive insurance options
Matching contributions through the 401(k) plan and the share purchase plan
Paid time off for vacation, holidays, and sick time
Paid parental leave
Learning opportunities and tuition assistance
Wellness and Well being programs

Employment offers in the U.S. are contingent upon successfully completing a background investigation
Depending on role and/or federal government security clearance requirements, background investigations may include a credit check
CGI considers qualified applicants with arrest and conviction records in accordance with local regulations and ordinances

CGI provides consideration for employment without regard to protected characteristics
Reasonable accommodations are provided to qualified individuals with disabilities
If you need an accommodation to apply in the U.S., email [email protected] and reference the Position ID

Mid-Level Full-Stack AI Engineer

Job Description