Principal MLOps Platform Engineer

As a Principal MLOps Platform Engineer, you will:

• Lead the evolution of enterprise Machine Learning and AI platforms
  
• Design scalable platform architecture for AI Agents and Vector Database implementations
  
• Evaluate and operationalize new platform capabilities and emerging Databricks features
  
• Establish engineering standards and governance for production-grade GenAI applications
  
• Design and manage Feature Stores, Model Registries, and Vector Search infrastructure
  
• Enable Retrieval Augmented Generation workflows across enterprise AI use cases
  
• Mentor senior engineering teams on platform design patterns, code quality, and architecture
  
• Translate AI and ML engineering requirements into robust engineering roadmaps
  
• Drive automation, scalability, and operational excellence across AI infrastructure
  
• Collaborate with cross-functional teams to enable production-ready AI solutions
  

What You Bring to the Table:

• 10+ years of experience across Data Engineering, MLOps, and AI Infrastructure
  
• Deep expertise with Databricks AI Stack including MLflow, Mosaic AI, Unity Catalog, Feature Store, Model Serving, and Vector Databases
  
• Advanced knowledge of Apache Spark internals, structured streaming, and performance optimization
  
• Strong experience with AWS infrastructure including EC2 and GPU-based compute environments
  
• Expert-level Python programming skills with hands-on PyTorch experience
  
• Strong experience with Terraform and Terragrunt for infrastructure automation
  
• Hands-on expertise with Docker and Kubernetes
  
• Experience building CI/CD pipelines using GitHub Actions
  
• Strong observability and monitoring experience using Datadog
  
• Proven experience operationalizing traditional ML and Generative AI workloads
  

You Should Possess the Ability to:

• Architect and scale enterprise-grade ML and AI platforms
  
• Optimize distributed compute workloads for large-scale processing
  
• Build low-latency, high-concurrency model serving systems
  
• Bridge experimental ML development with production-grade engineering
  
• Drive technical leadership and mentor engineering teams
  
• Translate business and AI requirements into scalable technical solutions
  

What We Bring to the Table:

• Opportunity to build cutting-edge enterprise AI and GenAI platforms
  
• Exposure to advanced Databricks, MLOps, and cloud-native technologies
  
• A highly collaborative and innovation-driven engineering environment
  
• Opportunities to shape enterprise AI strategy and technical standards
  

Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Asha Krishnan
Phone: +31 20 369 0609 ; Extn :146
Email:
LinkedIn: https://www.linkedin.com/in/asha-krishnan