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AI Engineer – Core Platforms
American Express. Implement model monitoring and evaluation techniques to improve AI system performance over time .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in implementing and monitoring AI systems, ensuring compliance with governance and security standards. Proficient in deploying machine learning models and managing CI/CD pipelines within cloud-native environments.
Highest-signal resume keywords
Machine LearningAI TechnologiesPython ProgrammingCI/CD PipelinesKubernetes
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningAI TechnologiesPython ProgrammingData ProcessingMLOpsLLMOpsCI/CDContainerizationModel EvaluationLarge Language Models
Tools & Technologies
KubernetesCI/CD ToolsContainerization ToolsMonitoring ToolsArtifact Management
Industry Keywords
AI GovernanceCompliance RequirementsModel MonitoringProduction AI SystemsCloud-Native Infrastructure
Tech Stack
Tools & technologiesCloudDistributed SystemsKubernetesPython
About the role
Key responsibilities & impact- Implement model monitoring and evaluation techniques to improve AI system performance over time
- Ensure AI solutions adhere to governance, security, and compliance requirements
- Support and troubleshoot AI models and data processing pipelines in production
- Collaborate with product and business teams to align technology initiatives with business objectives
- Perform standard tasks within established procedures and guidelines with some independence for routine tasks
- Develop and integrate components of production AI systems, including ML models or LLM-based services
- Apply enterprise standards for observability, safety, and compliance in implemented AI components
- Implement and support model packaging, validation, versioning, deployment, monitoring, and rollback using approved templates and controls
- Contribute to CI/CD, container, Kubernetes, registry, testing, and telemetry configurations for assigned workloads
- Troubleshoot common implementation issues and escalate complex design, optimization, or production problems to senior engineers
Requirements
What you’ll need- 2+ years software development, including hands-on experience in machine learning, AI technologies, and Agentic AI solutions
- Bachelor's degree in Computer Science, Machine Learning, Data Science, and/or comparable experience; advanced degree preferred
- Knowledge of Python and data processing technologies
- Working knowledge of machine learning techniques and model evaluation approaches
- Foundational working knowledge of MLOps or LLMOps, containers, Kubernetes fundamentals, CI/CD, artifact management, testing, and monitoring
- Basic understanding of GPU resource needs, runtime dependencies, scheduling constraints, and enterprise security and change controls
- Experience working with large language models, especially GPT-3.5/4 or similar AI models
- Experience with Python or R
- Experience deploying AI models and pipelines using machine learning operations tools
- Experience with CI/CD pipelines and containerized deployments
- Experience developing and deploying machine learning or LLM-enabled applications in production or near-production environments
- Practical experience with distributed systems concepts, APIs, and cloud-native infrastructure supporting AI workloads
- Moderate expertise in a specific technical domain
- Practical experience contributing to software, infrastructure, container, data, or machine learning deployment and automation work
- Exposure through project, internship, or practical work to containerized deployment, artifact repositories, automated testing, monitoring, versioning, or rollback
- Employment eligibility to work with American Express in the United States is required; the company will not pursue visa sponsorship
Benefits
Comp & perks- Competitive base salaries
- Bonus incentives
- 6% Company Match on retirement savings plan
- Free financial coaching and financial well-being support
- Comprehensive medical, dental, vision, life insurance, and disability benefits
- Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
- 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy
- Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
- Free and confidential counseling support through our Healthy Minds program
- Career development and training opportunities