Forward Deployed Application/ ML Engineering Expert

SAP•Stanford, CA

1d•$198,200 - $420,000•Hybrid

About The Position

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 being embedded directly within customer environments and fast-moving delivery teams. You work closely with customers to translate ambiguous business and operational requirements into secure, scalable, and reliable solutions, to solve complex real world business problems at speed 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. Working closely with product, data, ML, and customer teams, you apply modern AI assisted engineering practices and architectural guardrails aligned with SAP standards to enable responsible and scalable AI adoption.

Requirements

Extensive 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
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.
Solid architectural foundation across cloud platforms, distributed systems, scalability, security, and reliability.
Experience owning solutions across the full application lifecycle, from design and implementation to deployment and production operations.
Ability to work effectively with cross functional teams and customer stakeholders, communicating complex technical topics clearly.
Learning mindset, technical leadership, and accountability in high impact, ambiguous environments
You demonstrate a proactive approach to leveraging AI in everyday workflows, ensuring high‑quality outputs through thoughtful context design and system integration

Responsibilities

Design, develop, and operate production‑grade, cloud‑native enterprise applications integrating AI capabilities such as large language models, retrieval‑augmented generation, 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