Job description
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 (Py. Torch, Tensor. Flow, 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