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Campus Graduate Masters Engineer - AI Engineer , Enterprise Technology Services- Palo Alto, CA

Job in Palo Alto, Santa Clara County, California, 94306, USA
Listing for: Aimlroles
Full Time position
Listed on 2026-10-18
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 120000 - 160000 USD Yearly USD 120000.00 160000.00 YEAR
Job Description & How to Apply Below
Business Unit / Role Specific Info

The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues.

We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.

At American Express, we empower technologists to learn, innovate, and make an impact from day one. As an AI Engineer I in Enterprise Technology Services, you’ll join a full-time graduate program and contribute to technology work that helps teams explore, build, test, and responsibly scale AI-enabled solutions.

In this role, you may support work across machine learning, generative AI, intelligent automation, data pipelines, retrieval patterns, model evaluation, LLM integrations, AI agents, agentic workflows, and AI-enabled software features. You’ll collaborate with engineering, product, data, security, risk, and business partners to help deliver enterprise AI solutions responsibly, reliably, and securely.

Responsibilities & What Type of Work to Expect
  • Support the development, testing, and integration of AI / ML models, LLM integrations, intelligent services, or data retrieval pipelines under guidance.
  • Assist with data collection, preprocessing, transformation, and validation to support model training, testing, evaluation, and implementation.
  • Contribute to debugging and improving AI enabled solutions to strengthen performance, reliability, explainability, maintainability, and quality.
  • Support AI capabilities such as model training workflows, inference endpoints, prompt-based interactions, evaluation routines, retrieval patterns, AI agents, or agentic workflows.
  • Collaborate with engineering, product, data, risk, security, and business partners to implement AI-driven solutions aligned to business requirements.
  • Document model parameters, prompts, assumptions, data pipelines, integrations, and technical decisions to support reproducibility and knowledge sharing.
  • Participate in Agile development practices, including sprint planning, stand-ups, demos, retrospectives, code reviews, and team ceremonies.
  • Assist in ensuring AI systems and AI-enabled features align with enterprise expectations for reliability, safety, governance, security, compliance, and appropriate escalation.
Minimum Qualifications
  • Must have earned a Master’s degree in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Computer Engineering, Software Engineering, or another technical field before the full-time start date.
  • Knowledge of Python and foundational data processing technologies.
  • Foundational understanding of computer science concepts, including data structures, algorithms, object-oriented programming, debugging, testing, and problem solving.
  • Foundational understanding of machine learning concepts such as supervised learning, unsupervised learning, model training, evaluation, feature engineering, and experimentation.
  • Introductory understanding of modern AI systems, including LLM APIs, prompt-based interactions, retrieval patterns, AI powered tools, or generative AI applications.
  • Ability to support AI/ML development, testing, documentation, integration, or data pipeline activities…
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