AI/ML Engineer (Full Stack)

CGI is actively seeking an AI/ML and Emerging Tech Expert to join our Emerging Technologies Practice and lead the design and delivery of AI driven applications across our Federal Portfolio. You will work end to end-from proofs of concept to production-partnering with solution architects, data scientists, and engineering teams to turn ideas into scalable, secure solutions. This role blends full stack engineering with modern AI/ML, integrating generative AI and advanced analytics within Azure, AWS, and GCP to achieve tangible business outcomes. If you are a creative problem solver who thrives in fast moving, highly collaborative environments, come help us push the boundaries of AI and emerging technologies.

• This position is located in our Fairfax, VA or Lafayette, LA office; however, a hybrid working model is acceptable
• Your future duties and responsibilities:
• AI/ML Solutioning & Delivery
• Design, build, and deploy AI/ML solutions and generative AI applications; architect complex AI pipelines.
• Harness large datasets; conduct data mining/analysis; design algorithms and simulations; optimize models for real world performance and cost.
• Full Stack Engineering
• Implement front end (HTML/CSS/JavaScript; React or Angular) and back end services (Python/Flask/Django; Node.js; Java) that integrate AI capabilities.
• Develop robust APIs and microservices; ensure seamless functionality and exceptional UX across platforms.
• Cloud & DevSecOps
• Deliver against strategic roadmaps for AI and Analytics architectures across Azure, AWS, GCP.
• Package and deploy via containerization (Docker, Kubernetes); automate CI/CD (Jenkins, GitLab) and IaC (Terraform, AWS CloudFormation).
• Establish best practices and patterns for AI & analytics; implement monitoring, observability, and model governance.
• Graph Database Development
• Design, implement, and optimize GraphDB solutions (e.g., Neo4j, Amazon Neptune) for AI driven applications.
• Integrate graph based data models into AI pipelines for knowledge graphs, entity relationships, and semantic search.
• Collaboration & Client Engagement
• Work closely with data scientists and software engineers to integrate AI into enterprise systems.
• Coordinate with client and engineering teams to build, monitor, and maintain solutions.
• Support client development opportunities and contribute to thought leadership and demos/POCs.

• Bachelor’s (required) or Master’s (preferred) in Computer Science, Software Engineering, Artificial Intelligence & Machine Learning, related field., * 2+ years designing, developing, and deploying AI/ML or advanced software solutions.
• Proven experience designing and integrating AI/GenAI into products and enterprise applications.
• Demonstrated success delivering full stack solutions that embed AI capabilities.
• Hands on experience with GraphDB engineering and development (Neo4j, Amazon Neptune, or similar).

Technical Skills

• Programming: Python (expert) plus Java
• ML/Deep Learning: TensorFlow, PyTorch; model training, tuning, serving, and monitoring.
• Generative AI: hands on with LLMs; prompt engineering; fine tuning; RAG patterns; vector databases.
• Web & APIs: HTML/CSS/JS; React or Angular; Node.js/Python/Java back ends; REST/GraphQL.
• DevOps/MLOps: Docker, Kubernetes, Terraform, AWS CloudFormation; CI/CD with Jenkins/GitLab/Bitbucket; testing frameworks; package managers.
• Cloud: Production experience on Azure, AWS, and GCP.
• Data: SQL and NoSQL databases; GraphDB; data pipelines; feature stores.

Professional

• Excellent problem solving, verbal and written communication.
• Ability to work independently and within agile teams.
• Strong collaboration skills across cross functional stakeholders.

Desired qualifications/non essential skills required:

• Advanced degree (MS/PhD) in AI/ML or related field.
• Certifications in Azure/AWS/GCP; Kubernetes, Terraform, or ML specific certifications are a plus.
• Deep proficiency in Generative AI, including RAG, LLM orchestration frameworks, and model lifecycle governance.
• Portfolio of successful AI projects; evidence of thought leadership (POCs, publications, OSS contributions).
• Familiarity with federal sector standards (e.g., secure SDLC, data governance, compliance frameworks) and industry AI use cases.
• Strong client facing skills: solution storytelling, demos, and executive level presentations.

Skills:

• AWS AI Services
• AWS Machine Learning
• AWS Machine Learning
• Azure architecture
• Cloud Computing
• English
• Security Infrastr Service Ctr