Senior AI Engineer

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