Mid-Level Full-Stack AI Engineer

CGI is hiring a mid-level full-stack AI engineer to design, build, and deploy production AI applications using modern full-stack tooling and generative AI.

Responsibilities

• Lead end-to-end design, development, and deployment of AI-powered applications spanning 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 front-end applications using Angular
• Design and implement generative AI, LLM-based solutions, NLP, document classification, OCR, and conversational AI
• Drive machine learning work including inference, training, fine-tuning, and optimization for reliable production capabilities
• Develop and optimize RESTful APIs, system integrations, and database solutions to support interoperability, performance, and scalability
• Implement and maintain CI/CD pipelines and containerized deployments using Docker, Kubernetes, and cloud technologies
• Partner with product managers, data scientists, UI/UX designers, and engineering teams to translate business needs into technical designs and AI feature delivery
• Lead technical development of client-focused AI use cases leveraging CGI’s AI Platform, from solution design through production deployment
• Monitor, troubleshoot, and optimize production applications to ensure availability, security, reliability, performance, and operational efficiency
• Mentor junior engineers and participate in architecture and design reviews; guide teams and champion software engineering best practices

Requirements

• 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 of hands-on experience building AI-powered products involving generative AI, NLP, document classification, chatbots, OCR, or related intelligent automation
• Demonstrated experience with machine learning concepts, LLM inference, model integration, and deploying AI-enabled applications
• Strong experience designing and developing RESTful APIs, integrating distributed components, and applying software architecture and system design principles
• Hands-on experience with Docker and Kubernetes, including production deployment and container orchestration concepts
• Proficiency with relational and non-relational databases, including design, querying, performance tuning, and optimization
• Experience leveraging cloud platforms such as Microsoft Azure or Google Cloud Platform (GCP) to develop, deploy, manage, and scale AI applications
• Knowledge of secure development practices, data privacy regulations, compliance requirements, and responsible AI principles
• Strong analytical, troubleshooting, communication, and collaboration skills, including ownership of deliverables and the ability to guide junior team members in a fast-paced environment

Technologies

• Python, Angular
• Machine learning, generative AI, large language model (LLM)
• Natural language processing (NLP), document classification, optical character recognition (OCR), conversational AI
• RESTful APIs, CI/CD, Docker, Kubernetes
• Cloud technologies
• 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

Strongly Preferred

• Experience building production-grade applications using LLM frameworks, orchestration libraries, or AI development tools such as LangChain and Hugging Face
• Hands-on RAG implementation, including vector databases, embeddings, prompt engineering, or AI agent architectures
• Experience with fine-tuning, model evaluation, MLOps, and monitoring AI models in production
• Experience building automated CI/CD pipelines, testing frameworks, and deployment workflows using GitHub Actions, Azure DevOps, or similar tools
• Experience designing and deploying AI solutions using Microsoft Azure AI services, Google Cloud AI services, or related cloud-native AI technologies
• Demonstrated ability to lead technical feature development, mentor engineers, contribute to architecture decisions, and deliver customer-focused AI solutions

Location

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

Compensation

• USD 79,600 - 109,500 per year

Benefits

• 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

Contingencies and Eligibility

• U.S. offers of employment are contingent on successful completion of a background investigation
• Some background investigations may include a credit check based on role and/or federal government security clearance requirements
• Qualified applicants with arrests and conviction records will be considered in accordance with local regulations and ordinances

Equal Opportunity and Accommodation

• Employment consideration is provided without regard to race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation, gender identity or expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, or physical attributes
• CGI provides reasonable accommodations to qualified individuals with disabilities
• To request an accommodation to apply in the U.S., email [email protected] and reference the Position ID

CGI is required in some jurisdictions to include a reasonable estimate of the compensation range, which may vary based on skill set, level, experience, relevant training, and licensure or certifications.