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About the Role

In this role, you design, build, and operate AI-native enterprise applications that combine cloud-native software engineering with production-grade machine learning and agentic AI capabilities, embedded directly within customer environments and fast-moving delivery teams. You translate ambiguous business and operational requirements into secure, scalable, and reliable solutions — owning technical delivery from discovery and prototyping through deployment, stabilization, and successful handover to platform or operations teams. You are accountable for the technical quality, reliability, and impact of application solutions within your scope and apply modern AI-assisted engineering practices and architectural guardrails aligned with SAP standards to enable responsible and scalable AI adoption.

Responsibilities

Design, develop, and operate production-grade, cloud-native enterprise applications integrating AI capabilities such as large language models, retrieval-augmented generation (RAG), and agent-based workflows.
Embed directly into customer projects and fast-moving cross-functional teams to rapidly understand business processes, technical landscapes, and operational challenges.
Translate business and product requirements into robust application architectures, balancing speed, quality, security, and long-term maintainability.
Rapidly prototype, iterate, and productionize solutions in customer environments, adapting reference architectures and reusable assets to real-world enterprise constraints.
Own application delivery end-to-end — from problem framing and prototyping through deployment, observability, and production operations.
Apply AI-assisted engineering practices, evaluation frameworks, and architectural guardrails to ensure compliant, trustworthy, and high-quality solutions.
Ensure delivery milestones, quality standards, and technical objectives are met, proactively managing risks and technical escalations within scope.
Act as a key technical interface to customers and internal stakeholders, clearly communicating solution approaches, trade-offs, and progress.
Contribute to engineering standards, best practices, and reusable components to improve efficiency and consistency across solutions.

Requirements

10+ years of hands-on experience in software and application engineering for cloud-native, enterprise, and SaaS environments, with strong knowledge of architectural principles such as scalability, security, and reliability.
Proven ability to design and deliver AI-native applications, utilizing large language models, RAG architectures, vector databases, and agentic systems to innovate enterprise workflows.
Strong proficiency in widely used AI/ML Python libraries and frameworks, with exposure to data pipelines and MLOps practices.
Skilled in integrating Agentic AI into complex business processes, ensuring responsible and effective use of AI agents within enterprise operations.
Strong problem-solving skills, critical thinking, and exposure to design thinking practices; proven ability to mentor teams and establish development guardrails and best practices.
Proven ability to mentor and inspire teams, establish best development guardrails and practices, and drive engineering culture across delivery teams.
Exposure to SAP AI technologies such as SAP AI Core, Vectorization, Joule Studio, RPT-1, and Business Data Cloud is a strong advantage.
Experience owning solutions across the full application lifecycle — from design and implementation to deployment and production operations.
Strong collaboration and communication skills to work effectively with cross-functional teams and customer stakeholders on complex technical topics.
Learning mindset, technical leadership, and accountability in high-impact, ambiguous environments; you proactively leverage AI in everyday workflows to ensure high-quality outputs.

Skills

AI-native enterprise applications
Cloud-native software engineering
Production-grade machine learning
Agentic AI capabilities
Large language models
Retrieval-augmented generation (RAG)
Agent-based workflows
Application architectures
AI-assisted engineering practices
AI/ML Python libraries and frameworks
Data pipelines
MLOps practices
SAP AI technologies (SAP AI Core, Vectorization, Joule Studio, RPT-1, Business Data Cloud)
Collaboration
Communication

Location

New York City, NY

Work Type

Hybrid
Regular Full Time

Experience Level

10+ years of experience
Professional

Salary/Compensations

176300-374200 USD

Benefits

Constant learning
Skill growth
Great benefits
Team that wants you to grow and succeed
SAP North America Benefits

About the Company

We help the world run better at SAP.
SAP is a cloud company with two hundred million users and more than one hundred thousand employees worldwide, purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development.
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively.
Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management.

Equal Opportunity

We win with inclusion.
SAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best.
At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential.
We ultimately believe in unleashing all talent and creating a better world.
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities.
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, age, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability.