We are seeking a highly skilled Senior Agentic AI Engineer to design, develop, and deploy production-grade agentic AI systems on Azure cloud infrastructure. The ideal candidate will have extensive experience building autonomous AI agents, deploying complex AI solutions to production, and implementing robust CI/CD pipelines.

 Key Responsibilities

- Design and develop sophisticated agentic AI systems capable of autonomous decision-making and task execution

- Architect and implement production-grade AI solutions using Azure services (Azure Functions, Azure OpenAI, Azure Cognitive Services, etc.)

- Build and maintain CI/CD pipelines using Azure DevOps and/or GitHub Actions for automated testing and deployment

- Develop scalable data processing workflows using Azure Databricks and Apache Spark

- Implement comprehensive testing strategies for AI applications including unit tests, integration tests, and performance testing

- Optimize AI agent performance, reliability, and cost-efficiency in production environments

- Design and implement monitoring, logging, and observability solutions for AI systems

- Mentor junior engineers and lead technical discussions on AI architecture and best practices

- Collaborate with cross-functional teams to integrate AI agents into existing systems

- Implement security best practices including managed identities, Key Vault integration, and RBAC

 Required Skills & Qualifications

Technical Expertise:

- 5 to 8 years of experience in AI/ML engineering with at least 2+ years focused on agentic AI or autonomous systems

- Expert-level proficiency in Python and advanced knowledge of SQL

- Deep understanding of Azure cloud services (Azure Functions, Azure OpenAI, Azure ML, App Services, Storage, Key Vault)

- Extensive hands-on experience with Azure Databricks for large-scale data processing and ML workflows

- Proven track record of deploying and maintaining AI systems in production environments

- Strong experience building CI/CD pipelines using Azure DevOps and/or GitHub Actions

- Proficiency in containerization technologies (Docker, Kubernetes/AKS)

AI/ML Knowledge:

- Strong foundation in Machine Learning, Natural Language Processing, and Deep Learning

- Experience with large language models (LLMs) and prompt engineering

- Knowledge of multi-agent systems

- Understanding of RAG (Retrieval-Augmented Generation) architectures

- Experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn, Transformers)

Problem-Solving & Quality:

- Exceptional analytical and problem-solving skills with ability to debug complex distributed systems

- Experience designing and implementing comprehensive test suites for AI applications

- Strong understanding of software engineering best practices (clean code, design patterns, SOLID principles)

- Experience with monitoring tools (Application Insights, Log Analytics, Grafana)

 Preferred Qualifications

- Azure certifications (Azure AI Engineer Associate, Azure Solutions Architect)

- Experience with microservices architecture

- Knowledge of MLOps practices and tools (MLflow, Azure ML Pipelines)

- Experience with vector databases and semantic search