We are looking for an AI Engineer with strong experience in production deployment of AI systems, CI/CD automation, and scalable AI engineering practices. Candidates should have hands-on experience operationalizing machine learning and generative AI applications in enterprise environments.
Responsibilities:
Build and deploy AI/ML applications into production environments.
Design and maintain CI/CD pipelines for AI/ML workloads.
Manage model lifecycle, testing, monitoring, and deployment automation.
Work with cloud-native AI infrastructure on AWS.
Collaborate with engineering teams to productionize AI solutions.
Implement MLOps best practices and model governance.
Required Skills:
4–5 years of engineering experience.
Strong Python development experience.
Hands-on experience with AI/ML production deployment.
Experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, Azure DevOps).
Experience with Docker, Kubernetes, and containerization.
Strong AWS cloud experience.
Experience with monitoring and observability of AI systems.
Preferred Skills:
Experience with LLMs, RAG, or GenAI systems.
Exposure to MLflow, Kubeflow, SageMaker, or similar tools.
Financial domain experience.