AI/ML Operations Engineer

AI/ML Operations Engineer

About Our Company

Ameriprise India LLP has been providing client based financial solutions to help clients plan and achieve their financial objectives for 20 years. We are part of Ameriprise Financial Inc., a US financial planning company headquartered in Minneapolis with a global presence and diversified financial services leader with more than $1.5 trillion in assets under management, administration and advisement as of year-end 2024. The firm’s focus areas include Asset Management and Advice, Retirement Planning and Insurance Protection.

Be part of an inclusive, collaborative culture that rewards you for your contributions, and work with other talented individuals who share your passion for doing great work. You’ll also have plenty of opportunities to make your mark at the office and a difference in your community. So, if you're talented, driven and want to work for a strong, ethical company that cares, take the next step and create a career at Ameriprise India LLP.

Job Description

We are seeking a skilled and motivated AI/ML Platform Engineer to join our enterprise AI/ML platform team. The candidate will be responsible for supporting and operating AI/ML platforms such as Dataiku and Amazon SageMaker, while also contributing to the design and development of scalable AI/ML solutions across the enterprise.
The role requires a combination of platform engineering, cloud operations, automation, DevOps, and AI/ML service enablement. The engineer will work closely with data scientists, ML engineers, application teams, cloud engineering teams, and business stakeholders to enable secure, reliable, and governed AI/ML capabilities.
The successful candidate should have practical experience with AWS AI/ML services, platform operations, infrastructure-as-code, CI/CD pipelines, and enterprise-grade deployment patterns.

We are seeking a skilled and motivated AI/ML Platform Engineer to join our enterprise AI/ML platform team. The candidate will be responsible for supporting and operating AI/ML platforms such as Dataiku and Amazon SageMaker, while also contributing to the design and development of scalable AI/ML solutions across the enterprise.

The role requires a combination of platform engineering, cloud operations, automation, DevOps, and AI/ML service enablement. The engineer will work closely with data scientists, ML engineers, application teams, cloud engineering teams, and business stakeholders to enable secure, reliable, and governed AI/ML capabilities.

The successful candidate should have practical experience with AWS AI/ML services, platform operations, infrastructure-as-code, CI/CD pipelines, and enterprise-grade deployment patterns.

Key Responsibilities

Platform Operations and Support

• Support day-to-day operations of enterprise AI/ML platforms such as Dataiku and Amazon SageMaker.
• Manage platform availability, performance, access, configurations, monitoring, and operational health.
• Assist users with onboarding, troubleshooting, environment setup, and platform-related issues.
• Support upgrades, patching, environment maintenance, and operational improvements.
• Work with infrastructure, security, and cloud teams to ensure platform compliance with enterprise standards.

AWS AI/ML Services Enablement

• Work with AWS AI/ML services including: Amazon SageMaker Amazon Bedrock AWS AgentCore Amazon Q Amazon QuickSight Other related AWS analytics and AI/ML services
• Help design and implement AI/ML workloads using AWS-native capabilities.
• Support experimentation, prototyping, and production deployment of AI/ML and Generative AI use cases.
• Assist in implementing governance, guardrails, monitoring, and operational controls for enterprise AI/ML workloads.

Solution Design and Development

• Collaborate with data scientists, ML engineers, and business teams to design AI/ML solutions.
• Develop reusable platform components, automation scripts, templates, and deployment patterns.
• Support development of enterprise AI/ML use cases using Dataiku, SageMaker, Bedrock, and other AWS services.
• Help convert prototypes into scalable, maintainable, and production-ready solutions.
• Contribute to solution architecture discussions and technical design documentation.

DevOps, CI/CD, and Automation

• Develop and maintain CI/CD pipelines for AI/ML platform components and solution deployments.
• Use tools and technologies such as: Git Jenkins Bash scripting CloudFormation Terraform CI/CD workflow automation
• Implement infrastructure-as-code and configuration-as-code practices.
• Automate repetitive operational tasks to improve platform reliability and efficiency.
• Follow enterprise release management, change management, and deployment standards.

Monitoring, Governance, and Security

• Support implementation of monitoring, logging, alerting, and operational dashboards.
• Ensure AI/ML platforms and workloads follow enterprise security, compliance, and governance requirements.
• Assist in access management, role-based controls, audit logging, and environment isolation.
• Contribute to cost optimization, usage reporting, and platform adoption tracking.
• Support incident management, root cause analysis, and continuous improvement initiatives.

Reporting and Dashboarding

• Create and maintain dashboards and operational reports as required.
• Develop dashboards using Power BI for platform usage, adoption, operational metrics, or business reporting.
• Experience with dashboarding is preferred, though it is not the primary focus of the role.

Required Skills and Experience

• 3–5 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.

Preferred Skills

• Experience designing or deploying Generative AI solutions using AWS Bedrock or related services.
• Knowledge of LLM operations, prompt management, model evaluation, guardrails, and governance.
• Experience with ML lifecycle concepts such as data preparation, training, evaluation, deployment, monitoring, and retraining.
• Familiarity with containerization technologies such as Docker.
• Experience with Python or other scripting/programming languages.
• Exposure to enterprise security and compliance practices.
• Experience creating dashboards in Power BI.
• Familiarity with Agile delivery practices and enterprise change management.

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.

Full time(2:00p-10:30p)AWMPO AWMP&S President's OfficeTechnology

Ameriprise India LLP is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, genetic information, age, sexual orientation, gender identity, disability, military status, veteran status, marital status, pregnancy, family status or any other basis prohibited by law.

We are committed to fostering an inclusive and accessible recruitment process for individuals with disabilities. If you require a reasonable accommodation to participate in the application or interview process, speak to your recruiter to discuss how we can support you.