oracle
Senior Agentic AI Engineer - Core Platforms
American Express
New York City, USA
Full-time
Senior · 5+ years experience
Hybrid
Discovered 1 weeks ago
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Key Skills for This Role
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Qualifications
- Education and Knowledge
- 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 Big Data (Hadoop, Spark)
- Knowledge of natural language processing techniques like fuzzy wuzzy and models such as BERT, Transformer models, and their real-world applications
- 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
- Work Experience
- Experience in software development with a focus on machine learning, generative AI, Big Data, and prompt engineering
- Experience in working with large language models (LLMs), especially GPT-3.5/4 or similar AI models
- Experience in languages such as Python, R, Java, or C++
- Experience in deploying AI models and pipelines using machine leanring operations tools
- Experience in machine learning algorithms and experience applying them to real-world problems
- Experience in continuous integration/continuous deployment pipelines and containerized deployments
- Experience in building and maintaining data pipelines and extract, transform, and load 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 new, 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 is required as the company will not pursue visa sponsorship for these positions.
Responsibilities
- Mentors junior AI Engineers and cross-functional team of colleagues, fostering a culture of excellence and innovation
- Integrates AI models into production systems in collaboration with cross-functional teams, ensuring effective integration into existing production systems
- Maintains strict adherence to model governance, security, and compliance standards
- Provides guidance and support to junior engineers, fostering professional growth and development within the team
- Designs and implements AI/machine learning frameworks for data processing, focusing on prompt engineering and generative AI technologies
- Collaborates with engineers to deliver scalable AI solutions by integrating models that meet both technical and business requirements
- Translates business requirements into AI-driven technical solutions, ensuring that business needs are converted into actionable models and algorithms
- Develops reusable Big Data pipelines and AI-based systems, ensuring efficiency and consistency in data processing and model deployment
- Experiments with and deploys new natural language processing models to classify and analyze business-related text data, conducting research to improve text classification and analysis
- Creates end-to-end machine learning operations pipelines for scalable model deployment, facilitating seamless deployment, monitoring, and maintenance of AI models
- Collaborates and co-creates effectively with teams in product and the business to align technology initiatives with business objectives
- Designs and operates scalable production AI systems, integrating ML models, LLMs, and intelligent services across multiple components
- Leads development of AI capabilities such as robust inference services, retrieval pipelines (e.g., RAG), orchestration layers, and evaluation frameworks
- Ensures AI systems adhere to enterprise standards for reliability, safety, explainability, observability, and compliance, mentoring others on best practices
- Defines evaluation strategies, success criteria, benchmarks, and scorecards for LLM, RAG, agentic, and multimodal AI solutions across quality, safety, reliability, latency, and cost.
- Builds automated evaluation pipelines using curated datasets, synthetic test generation, human review, model-based grading, and deterministic checks; validates evaluators for consistency and bias.
- Establishes regression testing, release gates, and continuous evaluation to detect quality degradation, prompt or model drift, unsafe behavior, and changes introduced by models, data, tools, or orchestration.
- Partners with product, engineering, risk, and governance teams to convert use-case requirements and policy expectations into measurable acceptance criteria and traceable evidence.
- Performs failure analysis and communicates actionable findings, tradeoffs, and remediation priorities to engineering and business stakeholders.
Preferred Qualifications
- Bachelor's degree in computer science, Machine Learning, Data Science, and/or comparable experience; advanced degree preferred
About American Express
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