Lead ML Ops Engineer for Production AI Systems

SAP SE; Indiana; On-site; USD 120,000 - 180,000; Full time

Job summary

SAP SE is seeking an experienced AI/ML engineer to lead end-to-end development of production-ready AI solutions in a cloud environment. You will design pipelines, validate data quality, and work with stakeholders to ensure measurable business impact.

Ideal candidates bring hands-on experience in deploying AI systems, strong Python/SQL skills, and a track record of delivering reliable, scalable solutions. The role emphasizes collaboration across AI engineering, data validation, and governance

Qualifications

• Experience delivering AI/ML solutions into production.
• Strong programming skills in Python and SQL.
• Experience taking AI/ML from idea to deployment with validation and testing.
• Understanding of ML methods, model evaluation, and AI patterns.
• Experience building AI apps, copilots, or agent-based solutions is an advantage.
• Ability to structure ambiguous problems and make sound technical decisions.
• Strong communication with non-technical stakeholders and governance partners.

Responsibilities

• Design and implement pipelines and model workflows, and create orchestration systems.
• Develop integration components addressing large-scale business problems.
• Act as an ad-hoc data scientist to profile, clean, and validate data from enterprise systems.
• Define success metrics with product owners and engineers, and validate them through testing.
• Manage quality from discovery through release, including documentation and handover materials.

Skills

Ambiguity handling

Stakeholder communication

Team leadership

Problem solving

Strategic thinking

Tools

Python

SQL

Data pipelines

Job description

SAP SE is seeking an experienced AI/ML engineer to lead end-to-end development of production-ready AI solutions in a cloud environment. You will design pipelines, validate data quality, and work with stakeholders to ensure measurable business impact.

Ideal candidates bring hands-on experience in deploying AI systems, strong Python/SQL skills, and a track record of delivering reliable, scalable solutions. The role emphasizes collaboration across AI engineering, data validation, and governance