Ameriprise Financial - AI/ML Engineer

Role : AI/ML Operations Engineer

Required Skills and Experience :

- 2 to 4 years of experience in platform engineering, cloud engineering, DevOps, data engineering, or AI/ML platform support.

- Hands-on experience with Dataiku operations or similar enterprise data science platforms.

- Working knowledge of Amazon SageMaker operations, including notebooks, jobs, models, endpoints, pipelines, and related services.

- Understanding of AWS AI/ML services such as Bedrock, AgentCore, Amazon Q, QuickSight, and related cloud services.

- Experience supporting AI/ML workloads in an enterprise environment.

- Strong understanding of CI/CD patterns and DevOps practices.

- Hands-on experience with : Git, Jenkins, Bash scripting, CloudFormation, Terraform.

- Good understanding of AWS IAM, networking basics, logging, monitoring, and security best practices.

- Ability to automate operational tasks and build reusable deployment patterns.

- Strong troubleshooting, analytical, and problem-solving skills.

- Ability to work with cross-functional teams including data scientists, engineers, architects, and business users.

Tools and Technologies :

The candidate should have exposure to some or most of the following :

- Platforms : Dataiku, Amazon SageMaker

- AWS AI/ML Services : SageMaker, Bedrock, AgentCore, Amazon Q, QuickSight

- DevOps Tools : Git, Jenkins, Bash

- Infrastructure as Code : CloudFormation, Terraform

- Dashboarding : Power BI, QuickSight

- Cloud Platform : AWS

- Other : IAM, CloudWatch, Docker, CI/CD pipelines, automation scripts

In-Office Collaboration :

We are a client-centric, relationship-based business. Working together, in-person, is foundational to how we achieve results. By fostering a culture of face-to-face collaboration, idea sharing, productivity and personal connection, we deliver for our stakeholders clients, advisors, employees and shareholders. Our employees work in the office at least three (3) days per week, with flexibility to work from home two (2) days per week. Some roles may require additional in-office time or different in-office expectations, and specific requirements will be discussed during the hiring process.

(ref:hirist.tech)