Agentic AI Engineer - Global Infrastructure

American Express
New York, Phoenix
Workplace: HybridFull timeUSD 89,250 - 150,250 annuallyFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Collaboration","Troubleshooting","Cross-functional alignment","Independent judgment","Problem-solving"]

Build and optimize trained AI/ML models for production systems, enhancing data pipelines to support scalable AI processing. Design and review AI architectures aligned to enterprise standards, and implement model monitoring and evaluation to improve performance over time. Ensure AI solutions meet governance, security, and compliance requirements while troubleshooting production AI pipelines. Collaborate with product and business teams to align technology initiatives with business objectives and refine AI strategies.

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FursaFursa
American Express
American Express
1 day ago

Agentic AI Engineer - Global Infrastructure

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

Build and optimize trained AI/ML models for production systems, enhancing data pipelines to support scalable AI processing. Design and review AI architectures aligned to enterprise standards, and implement model monitoring and evaluation to improve performance over time. Ensure AI solutions meet governance, security, and compliance requirements while troubleshooting production AI pipelines. Collaborate with product and business teams to align technology initiatives with business objectives and refine AI strategies.
Location: New York, Phoenix
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develops and optimizes AI/ML models and ensures seamless integration with production environments.
  • •Builds and enhances data pipelines to support scalable and efficient AI processing.
  • •Participates in designing and reviewing AI architectures aligned with enterprise standards.
  • •Implements model monitoring and evaluation techniques to improve AI system performance over time.
  • •Supports troubleshooting of AI models and data processing pipelines in production while collaborating with product and business teams.

Pay and Benefits

Salary: USD 89,250 - 150,250 annually
Perks:Health InsuranceDentalVisionLife InsuranceDisability BenefitsRetirementParental LeaveRemote WorkPaid LeaveFinancial Coaching

Key Requirements

  • •Bachelor's degree in Computer Science, Machine Learning, Data Science, or comparable experience; advanced degree preferred.
  • •Knowledge of Python and data processing technologies.
  • •Familiarity with natural language processing techniques and models such as fuzzy wuzzy, BERT, and Transformer models.
  • •Experience with machine learning techniques and model evaluation approaches.
  • •Hands-on experience developing and deploying ML/LLM-enabled applications using LLMs (including GPT-3.5/4 or similar) in production or near-production environments.
Experience:Generative AIBig DataPrompt engineeringMachine learningLLMsProduction ML
Education:Bachelor's in Computer Science, Machine Learning, Data Science
Skills:CollaborationTroubleshootingCross-functional alignmentIndependent judgmentProblem-solving
Tech Stack:PythonRFuzzy wuzzyBERTTransformer modelsLLMsGPT-3.5/4RAGRetrieval-augmented generationModel monitoringCI/CDContinuous integration/continuous deploymentContainersContainerized deploymentsData pipelinesETLMLOpsDistributed systemsAPIsCloud-native infrastructure

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

American Express
Provides global payment, credit, and travel-related financial services for consumers and businesses. Best known for its charge and credit cards, merchant payment network, and premium customer rewards and servicing.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: New York City, United States
Founded: 1850
WebsiteLinkedIn