Senior Agentic AI Engineer – Core Platforms

American Express

. Design, develop, and maintain evaluation frameworks for LLM, RAG, agentic, and multimodal AI and machine learning solutions .

Posted 10/14/2026full-timeUnited StatesSenior💰 $123,000 - $215,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI and machine learning frameworks, with a strong focus on model governance, evaluation methodologies, and production deployment. Proficient in integrating AI models into scalable systems while mentoring junior engineers and collaborating with cross-functional teams.

Highest-signal resume keywords

Machine Learning TechniquesNatural Language ProcessingAI System ArchitecturesMLOps PipelinesBig Data Technologies

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Hard Skills

PythonMachine LearningAI TechnologiesData ProcessingNLP TechniquesHadoopSparkCI/CD PipelinesGenerative AIETL Processes

Soft Skills

MentoringCollaborationCommunication

Tools & Technologies

BERTTransformer ModelsGPT-3.5/4Containerized DeploymentsCloud-Native Infrastructure

Industry Keywords

Model GovernanceEvaluation FrameworksAutomated TestingModel DriftQuality Assurance

Tech Stack

Tools & technologies

CloudDistributed SystemsETLHadoopJavaPythonSparkC++

About the role

Key responsibilities & impact

Design, develop, and maintain evaluation frameworks for LLM, RAG, agentic, and multimodal AI and machine learning solutions
Mentor junior AI engineers and cross-functional colleagues
Integrate AI models into production systems with cross-functional teams
Maintain adherence to model governance, security, and compliance standards
Design and implement AI/machine learning frameworks for data processing, prompt engineering, and generative AI
Translate business requirements into AI-driven technical solutions, models, and algorithms
Develop reusable Big Data pipelines and AI-based systems
Experiment with and deploy NLP models to classify and analyze business-related text data
Create end-to-end MLOps pipelines for scalable model deployment, monitoring, and maintenance
Design and operate scalable production AI systems integrating ML models, LLMs, and intelligent services
Lead development of inference services, retrieval pipelines such as RAG, orchestration layers, and evaluation frameworks
Define evaluation strategies, success criteria, benchmarks, and scorecards across quality, safety, reliability, latency, and cost
Build automated evaluation pipelines using curated datasets, synthetic test generation, human review, model-based grading, and deterministic checks
Establish regression testing, release gates, and continuous evaluation to detect quality degradation, model drift, unsafe behavior, and changes from models, data, tools, or orchestration
Partner with product, engineering, risk, and governance teams to establish measurable acceptance criteria and traceable evidence
Perform failure analysis and communicate findings, tradeoffs, and remediation priorities to engineering and business stakeholders

Requirements

What you’ll need

5+ years' experience in software development, including hands-on experience in machine learning, AI technologies, and agentic 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 such as Hadoop and Spark
Knowledge of natural language processing techniques such as fuzzy wuzzy and models such as BERT and Transformer models
Advanced knowledge of machine learning techniques and performance optimization
Strong understanding of AI system architectures, including LLM ecosystems, retrieval systems, orchestration frameworks, and evaluation methodologies
Experience with machine learning, generative AI, Big Data, and prompt engineering
Experience with LLMs, especially GPT-3.5/4 or similar AI models
Experience with Python, R, Java, or C++
Experience deploying AI models and pipelines using machine learning operations tools
Experience with machine learning algorithms and applying them to real-world problems
Experience with CI/CD pipelines and containerized deployments
Experience building and maintaining data pipelines and ETL processes
Experience delivering end-to-end AI systems in production, including design and operational ownership
Experience with distributed systems design, scalable APIs, and cloud-native AI infrastructure, including monitoring and optimization
Advanced expertise in a technical domain and moderate expertise in a different technical domain
Experience building evaluation harnesses and automated test pipelines for LLM, RAG, or agentic applications using production-representative datasets
Experience designing human-in-the-loop and model-based evaluation workflows, including calibration, error analysis, and validation of evaluation quality
Experience integrating evaluation results into CI/CD, release readiness, production monitoring, and governance evidence
Employment eligibility to work with American Express in the United States; American Express 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
Global in-person and virtual collaboration flexibility through Amex Flex