Senior AI Engineer I - Global Dining

Role overview

Responsibilities

• Design, build, and operate scalable AI systems integrating ML models, LLMs, retrieval, and intelligent services.
• Develop RAG, agent orchestration, tool integrations, context management, structured outputs, and evaluation frameworks.
• Integrate AI into production systems and own implementation, testing, deployment, monitoring, maintenance, and improvement.
• Build evaluation and safety mechanisms, including regression testing, guardrails, permissions, validation, and recovery.
• Design for latency, throughput, availability, scalability, security, observability, cost, and failure modes.
• Translate customer and business needs into AI solutions for dining discovery, reservations, hospitality workflows, and servicing.
• Evaluate emerging AI technologies and establish reusable engineering patterns and standards.
• Provide technical leadership through architecture reviews, code reviews, and mentoring.

Qualifications

• Bachelor’s degree in a related technical field or equivalent practical experience; advanced degree preferred.
• Significant experience building and operating production AI/ML systems, including generative AI, LLM applications, or agentic systems.
• Strong Python proficiency and experience with an additional language such as Go, TypeScript, or Java.
• Understanding of LLMs, NLP, RAG, tool calling, structured generation, context management, orchestration, and evaluation.
• Experience integrating commercial or open-source LLMs into real-world applications.
• Experience designing scalable distributed, API-driven production systems.
• Experience building data pipelines and ETL using Spark, Hadoop, or comparable frameworks.
• Experience deploying and operating AI models and pipelines with MLOps, CI/CD, and containerized infrastructure.
• End-to-end production system ownership and experience mentoring engineers.
• Strong communication, collaboration, pragmatic decision-making, and customer focus.

Technical environment

• Languages include Python, Go, and TypeScript; experience with Java is also mentioned.
• Cloud and infrastructure include AWS and/or GCP, Kubernetes, and Docker.
• Platforms and tools include LangGraph and LangChain; APIs include REST and gRPC.
• Distributed systems include event-driven architectures such as Kafka; data processing includes large-scale pipelines.
• AI/ML topics include LLMs, RAG, vector storage, prompt engineering, model evaluation, transformers, schema validation, and MLOps.
• AI-assisted development tools may be used for design, implementation, testing, debugging, and refactoring.

Work arrangements

• Benefits information describes flexible working arrangements that may be hybrid, onsite, or virtual depending on role and business need; the role’s specific arrangement is not stated.

About American Express Global Dining