AI Architect / MLOps Engineer (Azure AI Platform)
Trigent Software - Professional Services
2 - 5 years
Bengaluru
Posted: 27/12/2025
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Job Description
Location: Bangalore/Hyderabad (Hybrid/Remote)
Experience: 46 Years
Role Summary
We are seeking an AI Architect / MLOps Engineer to design, govern, and scale enterprise-grade AI systems on the Azure platform. The role focuses on building robust AI architectures with strong operational, security, and compliance foundations, while enabling reliable model lifecycle management and production readiness.
Key Responsibilities
- Define and implement AI reference architectures using Azure AI services and best practices.
- Design and build end-to-end MLOps pipelines for model development, versioning, evaluation, deployment, and rollback.
- Establish model lifecycle governance, including safety, policy controls, and compliance-by-design.
- Configure and manage monitoring for model accuracy, data/model drift, latency, availability, and cost optimization.
- Enable CI/CD pipelines for AI/ML workloads, ensuring repeatable and automated deployments.
- Collaborate with and guide engineering teams on scalable, secure, and production-ready AI patterns on Azure.
- Ensure adherence to enterprise security standards, data privacy, and regulatory requirements.
Required Skills & Qualifications
- Strong hands-on experience with Azure AI Foundry, Azure OpenAI, and Azure Machine Learning (Azure ML) concepts.
- Proven experience in MLOps , CI/CD for ML, and model evaluation frameworks.
- Experience with observability tools such as Azure Monitor, Application Insights, and Log Analytics .
- Solid understanding of security and governance including RBAC, private endpoints, network isolation, and compliance-by-design.
- Ability to translate business and architectural requirements into scalable AI solutions.
- Strong communication skills to mentor teams and influence architecture decisions.
Nice to Have
- Experience with enterprise AI governance frameworks and responsible AI practices.
- Exposure to cost management and optimization for AI workloads on Azure.
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