AI Engineer

Role Overview

We are seeking an AI Engineer to architect, develop, and implement intelligent systems based on large language models (LLMs), agent orchestration frameworks, and embedding-based information retrieval methods. This position requires combining practical engineering with strategic solution design to enable scalable cloud-native workflows.

Key Responsibilities

• Create applications that utilize LLM APIs for tasks such as summarization, question answering, and aiding decision-making processes.
• Design and implement agent-based workflows to automate multi-step tasks.
• Build embedding pipelines tied to vector databases to enhance retrieval-augmented generation (RAG) and search functionalities.
• Deploy AI components onto cloud platforms using containerization and continuous integration/continuous deployment (CI/CD) best practices.
• Oversee model performance in production environments and optimize for efficiency and cost-effectiveness.

Required Qualifications and Skills

• Two to four years of experience developing AI/ML applications.
• Proficient in Python programming, particularly involving integration with LLM APIs and prompt engineering workflows.
• Practical experience with Databricks technologies, including Spark SQL, PySpark, and Delta Lake, as well as Snowflake data platform.
• Working knowledge of agent orchestration tools, embedding representations, vector databases, and agentic frameworks.
• Familiarity with cloud-native architectures on Azure, API integration patterns, and CI/CD pipelines.

Inclusion and Equal Opportunity

Ecolab firmly supports a culture of inclusion and fairness. Our hiring, promotion, and workplace practices prioritize qualifications and performance without discrimination based on race, religion, color, creed, national origin, citizenship, gender identity, sexual orientation, marital status, age, disability, or genetic information. We are committed to providing equal opportunity employment to all applicants and employees.