Senior MLOps Gen AI Engineer

We are looking for a Senior MLOps Gen AI Engineer to support the development and deployment of AI tools.

You will work at the crossroads of data science, engineering, and cloud infrastructure to build scalable and automated AI systems that deliver business value. Your role will involve collaborating with data scientists, stakeholders, and cloud engineers to turn AI experiments into stable and efficient applications. Join us to contribute to predictive analytics, generative AI solutions, and interactive dashboards that empower business leaders.

Responsibilities

• Collaborate with data scientists to convert machine learning and generative AI experiments into scalable production pipelines
• Develop and maintain shared code repositories and reusable components
• Design and implement CI/CD pipelines in AWS or Azure for deploying models, APIs, and generative AI tools
• Build and manage data pipelines and DataOps processes
• Containerize applications with Docker and deploy them on cloud-native platforms
• Automate infrastructure provisioning using Terraform and manage database schemas in Azure and Snowflake
• Deploy and operate generative AI applications such as chatbots, retrieval-augmented generation systems, and predictive analytics tools
• Implement monitoring, observability, and explainability mechanisms to ensure system reliability
• Establish alerting, rollback strategies, and observability tools to maintain system stability
• Participate in code reviews and recommend improvements to workflows

Requirements

• Extensive experience in MLOps and data integration with 5 to 9 years in related roles
• Proven background in designing and deploying scalable machine learning production pipelines
• Competency in cloud platforms such as AWS and Azure for infrastructure and model deployment
• Skills in containerization technologies like Docker and infrastructure as code using Terraform
• Familiarity with data orchestration and management in Azure and Snowflake environments
• Knowledge of generative AI fundamentals and practical deployment experience
• Ability to collaborate effectively with data scientists and engineers to operationalize AI models
• Strong problem-solving skills and attention to system observability and reliability

Nice to have

• Experience with large language models (LLM)
• Understanding of retrieval-augmented generation (RAG) systems