Senior Support Engineer - AI/ML Platform and MLOps

Sr Support Engineer 1 – AI, LLM, Python, ML

Scope

• Position is focused on supporting and enhancing AI/ML platforms and MLOps pipelines for enterprise-scale applications.
• Build and manage end-to-end AI lifecycle workflows, including model training, validation, deployment, monitoring, and retraining.
• Work closely with Data Science, DevOps, Infrastructure, Platform Engineering, and Application teams.
• Ensure production AI systems are stable, observable, and compliant with governance standards.
• Support AI platform operations during steady state and drive continuous improvements.
• Enable reusable and standardized AI platform components for multiple use cases across the organization.
• Contribute to improving reliability, scalability, and performance of AI-driven systems.

Our Current Technical Environment

• Cloud Architecture: MS Azure
• AI/ML Platforms: Azure ML / OpenAI / MLflow (or similar)
• Programming: Python
• Data & Processing: SQL, Data Pipelines, REST APIs
• MLOps / DevOps Tools: CI/CD pipelines, Git, Azure DevOps
• Frameworks / Others: Model Monitoring, Logging, Experiment Tracking, Containerization (Docker), Kubernetes (preferred)

What You’ll Do

• Design, implement, and support AI/ML pipelines for training, testing, deployment, and inference workflows.
• Build and maintain MLOps frameworks for model versioning, experiment tracking, and reproducibility.
• Develop automation for model deployment, rollback, scaling, and lifecycle management.
• Establish model monitoring frameworks for performance, drift detection, data quality, and reliability.
• Collaborate with Data Scientists to operationalize models into production-ready systems.
• Integrate AI workflows into CI/CD pipelines for seamless deployment and updates.
• Troubleshoot production issues related to AI models, pipelines, and infrastructure; perform root cause analysis and implement permanent fixes.
• Ensure AI systems meet performance, scalability, security, and compliance requirements.
• Create reusable components and templates for standardizing AI deployment and operations.
• Implement logging, observability, and alerting mechanisms for AI services.
• Support governance requirements such as model traceability, auditability, and version control.
• Document AI platform processes, standards, and operational procedures.
• Provide guidance and support to cross-functional teams on AI platform usage and best practices.
• Drive continuous improvement in AI platform reliability, automation, and operational efficiency.

What We Are Looking For

• Bachelor’s degree in engineering, Computer Science, Data Science, or a related field.
• Minimum 6 years of overall IT experience, with at least 3+ years in AI/ML platform engineering, MLOps, or AI production support.
• Strong programming skills in Python, with experience in building automation and data/ML workflows.
• Hands-on experience with AI/ML platforms such as Azure ML, MLflow, or similar ecosystems.
• Experience in building and managing end-to-end ML pipelines and model lifecycle workflows.
• Good understanding of model deployment patterns, APIs, batch/real-time inference systems.
• Experience with CI/CD pipelines, version control (Git), and DevOps practices.
• Familiarity with containerization (Docker) and orchestration tools like Kubernetes (preferred).
• Strong understanding of model monitoring, drift detection, logging, and observability practices.
• Experience working with data pipelines, SQL, and data processing frameworks.
• Understanding of AI governance, model explainability, auditability, and compliance considerations.
• Ability to work collaboratively with data scientists, engineers, DevOps, and platform teams.
• Exposure to LLMs, generative AI workflows, or AI-driven automation use cases is an added advantage.

Our Values

If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success – and the success of our customers. Does your heart beat like ours? Find out here: Core Values

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

Experience Level

Senior Level