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
Technical Expertise
Required Skills & Qualifications
- 3 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
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Ecolab est comprometido con el trato justo e igualitario de todas las personas colaboradoras y postulantes, y con la promocin de los principios de igualdad de oportunidades en el empleo. Reclutaremos, contrataremos, promoveremos, transferiremos y brindaremos oportunidades de desarrollo con base en las calificaciones individuales y el desempeo laboral, en todos los aspectos relacionados con el empleo, la compensacin, los beneficios, las condiciones laborales y las oportunidades de crecimiento. Ecolab no discriminar a ninguna persona colaboradora ni postulante por motivos de raza, religin, color, credo, nacionalidad, estado de ciudadana, sexo, orientacin sexual, identidad y expresin de gnero, informacin gentica, estado civil, edad o discapacidad.
