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Specialized agentic AI, Azure, LLM and Databricks requirements reduce applicant pool despite mid-level seniority.
Role requires agentic AI, LLMs, and Azure production experience, making cross-industry transfers difficult.
Explicit 5–8 year requirement plus mandatory Azure, Databricks, LLM, CI/CD, and Kubernetes skills enforce strict filtering.
Design and develop autonomous agentic AI systems deployed on Azure cloud infrastructure with production-grade reliability.
Build and maintain scalable data processing workflows and CI/CD pipelines using Azure DevOps/GitHub Actions for automated testing and deployment.
Implement monitoring, performance optimization, security best practices, and lead technical discussions and mentoring within AI engineering teams.
5 to 8 years of AI/ML engineering experience with at least 2 years focused on agentic AI or autonomous systems.
Expert proficiency in Python and advanced SQL knowledge.
Deep experience with Azure cloud services (Azure Functions, Azure OpenAI, Azure ML, Databricks) and containerization (Docker, Kubernetes/AKS).
Proven experience deploying and maintaining production AI systems and building CI/CD pipelines on Azure DevOps and/or GitHub Actions.
Experienced in designing complex autonomous AI systems and operating ML workflows at scale on Azure cloud environment.
Strong hands-on expertise with agentic AI, multi-agent systems, LLMs, and implementing robust testing and observability for AI applications.
Senior-level engineer comfortable leading technical mentoring and cross-functional collaboration with a strong foundation in software engineering best practices.