Senior Full-Stack AI Engineer

CGI•Knoxville, TN

22h

About The Position

CGI is a global IT and business consulting services firm with professionals around the world helping clients achieve meaningful outcomes through technology, innovation, and industry expertise. At CGI, you’ll collaborate with talented colleagues in an ownership-driven culture where you can contribute to impactful solutions while continuing to grow your career. CGI is seeking a Senior Full-Stack AI Engineer to join our dynamic team and help design, build, and deliver scalable, AI-powered applications. In this role, you’ll work across the technology stack—from backend development, APIs, data pipelines, and LLM inference to modern frontend experiences and cloud-native deployment. You’ll combine machine learning expertise, software engineering practices, and system design knowledge to create intelligent, production-ready solutions that address real-world client challenges. As a senior member of the team, you’ll take a lead role in developing features and AI use cases, collaborating across product and technical teams, and mentoring junior team members. You’ll have the opportunity to work with generative AI, natural language processing, cloud platforms, and modern application architectures while helping shape solutions built on CGI’s AI platform. This role may be based in any CGI office, with Knoxville, Tennessee preferred.

Requirements

Bachelor's or master's degree in computer science, artificial intelligence, engineering, or a related field, or equivalent practical experience
5+ years of full-stack software development experience, including strong hands-on expertise with Python backend development and Angular frontend development
2+ years of hands-on experience building products or solutions using generative AI, NLP, document classification, conversational AI/chatbots, OCR, or related AI technologies
Hands-on experience with NLP libraries, AI/ML frameworks, LLM inference, model integration, and production AI application development
Strong understanding of Kubernetes concepts and experience deploying and managing containerized applications in production environments
Proficiency with relational and non-relational databases, including database design, performance tuning, and optimization techniques
Experience with cloud platforms such as Microsoft Azure or Google Cloud Platform (GCP) for deploying and scaling applications and AI workloads
Strong ownership and accountability with the ability to deliver production-ready systems in a fast-moving, iterative environment
Effective communication and collaboration skills, including the ability to explain complex technical concepts to technical and non-technical stakeholders
Strong problem-solving skills with knowledge of data privacy, security best practices, compliance requirements, and responsible AI considerations

Nice To Haves

Experience leading a small Agile/Scrum development team and maintaining delivery against sprint commitments
Experience designing enterprise-scale AI or generative AI platforms and reusable AI services
Experience with CI/CD automation, Docker, Kubernetes, observability, and modern cloud-native application architectures
Experience designing and implementing Retrieval-Augmented Generation (RAG), LLM-powered applications, or enterprise AI integrations
Demonstrated ability to mentor engineers and provide technical leadership across complex, cross-functional initiatives

Responsibilities

Lead the design, development, and deployment of end-to-end full-stack solutions for an AI platform, including data pipelines, model capabilities, APIs, and user-facing applications
Build and maintain scalable, efficient, secure, and production-ready backend services using Python
Train, fine-tune, evaluate, and perform inference with machine learning and generative AI models
Integrate AI and LLM capabilities into production applications while optimizing latency, performance, reliability, and scalability
Collaborate with product managers, data scientists, UI/UX designers, engineers, and other stakeholders to deliver high-impact features and client solutions
Build and deploy applications through CI/CD pipelines using containerization and orchestration technologies such as Docker and Kubernetes
Manage and optimize relational and non-relational databases to support application performance, scalability, and reliability
Design system integrations and ensure seamless interoperability across platform components and enterprise systems
Monitor and continuously improve production systems to maintain availability, performance, security, and operational reliability
Lead the technical design and delivery of customer use cases using the CGI AI platform while mentoring junior engineers and supporting Agile delivery