Senior Agentic AI Engineer

Rockwell Automation is a global technology leader focused on helping the world’s manufacturers be more productive, sustainable, and agile. With more than 28,000 employees who make the world better every day, we know we have something special. Behind our customers - amazing companies that help feed the world, provide life-saving medicine on a global scale, and focus on clean water and green mobility - our people are energized problem solvers that take pride in how the work we do changes the world for the better.

We welcome all makers, forward thinkers, and problem solvers who are looking for a place to do their best work. And if that’s you we would love to have you join us!

Job Description

Senior Agentic AI Engineer

Job Description

Rockwell Automation is looking for an experienced Agentic AI Engineer to serve as a technical leader within our Data Science and Innovation Organization. This role is crucial for executing our enterprise AI vision by architecting, implementing, and deploying sophisticated Generative AI and Agentic AI solutions. We are looking for someone who is specialized in Generative AI. This specialization includes RAG pipelines, agentic frameworks, and LLM implementation. You have a proven track record of leading high-impact projects, optimizing ML systems for performance, and building robust MLOps infrastructure in cloud-native environments.

You will report to the Director MLE and Data Science Innovation.

Key Responsibilities

Agentic Framework Development involves designing, engineering, and deploying production-ready multi-agent systems and services. These systems and services utilize modern frameworks such as Microsoft Semantic Kernel, Azure AI Foundry Agents, or Google Agent Development Kit (ADK).

Generative AI Pipeline Engineering (RAG):

Architect and implement scalable end-to-end Retrieval-Augmented Generation (RAG) pipelines. These pipelines include data ingestion, document processing, and embedding generation, such as using Azure OpenAI embeddings or Gemini embeddings. Additionally, they involve integration with vector and NoSQL databases.

Azure MLOps and Deployment: Lead the development of robust MLOps infrastructure for AI systems, leveraging Azure Machine Learning (AML) or Kubeflow for pipeline orchestration, alongside Docker for containerization. Deploy and manage scalable inference services on server less platforms like Azure Container Apps or Google Cloud Run.

Performance Optimization: Optimize model serving layers and high-throughput data processing pipelines, employing advanced libraries (e.g., Polars) to ensure ultra-low latency and efficient resource utilization across the cloud environment.

System Architecture & Security: involves designing and implementing secure system architectures for all new AI products. These architectures ensure strict compliance with enterprise-wide data governance and security policies through mechanisms such as PII filtering and guarded conversation frameworks.

Infrastructure Automation & CI/CD: Use Terraform for provisioning and manage Azure infrastructure-as-code. Implement centralized observability (logging and alerting) to support automated and reproducible Continuous Integration/Continuous Deployment (CI/CD) pipelines.

The Essentials - You Will Have

• Bachelor's Degree in Relevant Field

• Legal authorization to work in the U.S. We will not sponsor individuals for employment visas, now or in the future, for this job opening.

The Preferred - You Might Also Have:

• Typically requires a minimum of 8 of relevant professional experience, with a focus on AI/ML Engineering and Agentic AI product development.

• Master of Science in Business Analytics, Data Science, or a similar quantitative discipline.

• Expert-level proficiency in Python and SQL.

• Hands-on experience developing and deploying Generative AI solutions, RAG pipelines, and multi-agent frameworks, regardless of the underlying cloud vendor.

• Experience with major cloud platforms, specifically Microsoft Azure, Aws, or Google Cloud Platform (GCP).

• Worked on core MLOps and orchestration tools, including Docker, Airflow, and Kubeflow/Azure Machine Learning (AML).The

• Worked with vector search platforms like Azure Cosmos DB for PostgreSQL, Redis, Azure AI Search, or pgvector/Mongo Atlas.

• Familiarity with advanced statistical modeling techniques such as Causal Inference or Matrix Factorization.

• Experience optimizing large-scale data processing using libraries like Polars.

• Familiarity with Scaled Agile Framework (SAFe) methodologies.

What We Offer:

This position is part of a job family. Experience will be the determining factor for position level and compensation.

At Rockwell Automation we are dedicated to building a diverse, inclusive and authentic workplace, so if you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right person for this or other roles.

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We are an Equal Opportunity Employer including disability and veterans. 

If you are an individual with a disability and you need assistance or a reasonable accommodation during the application process, please contact our services team at +1 (844) 404-7247.

Rockwell Automation’s hybrid policy aligns that employees are expected to work at a Rockwell location at least Mondays, Tuesdays, and Thursdays unless they have a business obligation out of the office.