Principal AI Engineer

What you'll do

• Build and deploy production-ready Generative AI applications using LLMs, RAG architectures, and agentic workflows.
• Develop scalable APIs, microservices, and backend services to power AI-enabled enterprise platforms.
• Integrate AI capabilities into existing business systems and customer-facing applications.
• Manage and deploy AI workloads across cloud environments like Azure and AWS using Kubernetes.
• Establish CI/CD pipelines and implement MLOps best practices for monitoring and lifecycle management.
• Translate complex business requirements into technical solutions and scalable software architectures.
• Evaluate emerging AI technologies to identify opportunities for enterprise adoption and integration.

What we're looking for

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
• Experience developing enterprise applications using modern software engineering practices and SDLC environments.
• Strong proficiency in Python and modern application development frameworks.
• Experience building RESTful APIs and microservices.
• Knowledge of Generative AI technologies, LLMs, and AI application architectures.
• Experience with cloud platforms such as Azure and/or AWS.
• Knowledge of CI/CD pipelines, DevOps practices, and software release management.
• Experience with containerization and orchestration technologies such as Kubernetes and Docker.
• Experience building RAG solutions (preferred).
• Experience developing agentic AI workflows and autonomous AI systems (preferred).
• Knowledge of MLOps platforms and machine learning deployment practices (preferred).
• Familiarity with vector databases, prompt engineering, and AI evaluation frameworks (preferred).
• Exposure to enterprise security, governance, and responsible AI practices (preferred).