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:

- 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

Our Commitment to a Culture of Inclusion & Belonging
Ecolab is committed to fair and equal treatment of associates and applicants and furthering the principles of Equal Opportunity to Employment. We will recruit, hire, promote, transfer and provide opportunities for advancement based on individual qualifications and job performance in all matters affecting employment, compensation, benefits, working conditions, and opportunities for advancement. Ecolab will not discriminate against any associate or applicant for employment because of race, religion, color, creed, national origin,citizenship status, sex, sexual orientation, gender identity and expressions, genetic information, marital status, age, or disability.