Full Stack Developer

Job order - J - Permanent Full Time

Title Full Stack Developer

Category Software Development/ Engineering

City Dallas, Texas, United States

Job Description Full Stack Developer Position Description We're growing rapidly and are looking for Full Stack Developers to join our Telecommunications Sector.

We're a close knit team that has access to global resources. You'll have the opportunity to explore a wide range of industries, technologies, and geographies, all while enjoying the personal touch that our local operating approach offers. Growth at CGI is driven by your goals, so if you're looking for an inclusive place where you're empowered to chart your own path, then we'd love to meet you.

Location strongly preferred to be in Dallas or Plano, Texas.

• Design, develop, and maintain scalable backend applications and RESTful APIs using Python and FastAPI
• Build high performance, secure, and reusable API services supporting AI, analytics, and enterprise applications
• Develop integrations with Snowflake, Databricks, and cloud based data platforms
• Design and optimize data access layers supporting structured, semi structured, and large scale datasets
• Develop services that leverage Apache Iceberg tables and modern data lakehouse architectures
• Build event driven and asynchronous backend services where appropriate
• Optimize API performance, scalability, reliability, and security
• Implement authentication and authorization using OAuth2, JWT, Azure AD, or similar enterprise identity providers
• Collaborate with cloud engineers to deploy applications on Microsoft Azure using modern Dev Ops practices
• Participate in architecture reviews, code reviews, and technical design discussions

• Bachelor's degree in Computer Science, Engineering, or equivalent experience
• 5+ years of professional software development experience
• 5+ years of hands‑on Python development
• Strong experience developing production grade applications using FastAPI
• Strong understanding of REST API design and backend architecture
• Experience with asynchronous programming in Python
• Experience integrating applications with Snowflake
• Experience working with Databricks
• Experience using Apache Iceberg tables and modern lakehouse architectures
• Experience developing applications on Microsoft Azure
• Experience building AI enabled or GenAI applications
• Experience integrating with Large Language Models (Azure OpenAI, OpenAI, Anthropic, etc.)
• Experience with vector databases and Retrieval Augmented Generation (RAG)
• Experience with MLflow or MLOps practices
• Experience writing unit, integration, and automated tests
• Strong knowledge of SQL and database design
• Experience with containerization technologies such as Docker
• Excellent debugging, analytical, and problem solving skills
• Strong communication and collaboration skills

Preferred Qualifications

• Experience with Azure Kubernetes Service (AKS)
• Experience with Azure Functions or Azure App Services
• Experience with Azure API Management
• Experience with Azure Key Vault
• Experience with Azure Event Hubs or Service Bus
• Experience with Terraform or Infrastructure as Code
• Familiarity with Spark and Py Spark
• Experience with distributed systems and microservices architectures

• Python
• FastAPI
• REST APIs
• Snowflake
• Databricks
• Apache Iceberg
• Microsoft Azure
• SQL
• MLflow
• Azure OpenAI
• Lang Chain or similar AI frameworks

• AKS
• Git
• Docker
• CI/CD
• Azure Functions
• Azure API Management
• Azure Key Vault
• Azure Dev Ops
• Kubernetes
• Terraform
• Py Spark

• Strong ownership mindset
• Passion for building clean, maintainable, and scalable software
• Ability to work independently while collaborating effectively with cross functional teams
• Comfortable working in Agile environments
• Continuous learner with interest in AI, cloud technologies, and modern data platforms
• Strong attention to quality, security, and performance
• Experience supporting enterprise AI initiatives
• Experience building APIs that serve AI/ML models
• Experience working with large scale enterprise data platforms
• Exposure to telecom, financial services, or other large enterprise environments

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