Sr AI Engineer I
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Sr AI Engineer I
123,000–215,250 / Year
Location
Phoenix, AZ, United States • New York, NY, United States
Experience
Senior
Posted
Jul 7, 2026
Apply by
August 6, 2026
Applicants
0
Early applicantFull-timeHybrid
Job Description
The U.S. Consumer and Digital Technology (USCDT) Team brings together foundational strategic technology capabilities in digital experience engineering (Mobile and Web), AI/ML, marketing technology, enterprise communications, travel and lifestyle, and automation, grounded in our data technology model that prioritizes data governance. It employs a ground-breaking focus with development responsibilities for customer-facing capabilities that deepen and expand digital engagement, as well as core technical capabilities that cut across business lines and customer segments.
American Express Ads, Offers, and Dining Technology (AODT) brings together our advertising, offers, and dining platforms to elevate the Membership experience. The team drives the expansion of Amex Offers, the development of innovative digital advertising capabilities, and leads the end-to-end technology integration and platform development of our dining services—including Resy, Tock, and Rooam – to create seamless connections between diners, restaurants, and the broader American Express Membership ecosystem.
As part of Team Amex, you’ll experience a culture built on innovation, shared values, and an unwavering commitment to back our customers and colleagues. You’ll have the support, flexibility, and autonomy to make an impact while helping shape the future of how people discover, book, and enjoy dining experiences worldwide.
As a Senior AI Engineer – Agentic AI, you will be a core builder responsible for turning complex, ambiguous problems into production-grade agentic systems that operate on real financial data, serve real customers, and meet real regulatory requirements.
You will work end to end: shaping solutions with product and design, building and shipping production code, and owning what you deliver after launch. The scope of this role spans customer-facing LLM-powered features, agentic systems that automate financial workflows, and internal AI capabilities that enable other engineers to build with AI safely and efficiently.
This is not a research-only role. We are looking for engineers who are comfortable operating with autonomy, exercising sound judgment, and pushing the technical envelope within the realities of a regulated financial environment.
### Responsibilities
**What You’ll Do**
- Design, build, and ship LLM-powered and agentic product features that change how customers manage their finances.
- Build agentic AI systems that reason over context, invoke tools, take real actions, and recover gracefully from failure.
- Architect and implement production-grade RAG pipelines over sensitive financial data, with strict requirements for correctness, auditability, and safety.
- Contribute to shared AI infrastructure, including LLM services, agent orchestration frameworks, and evaluation and monitoring tooling, that scales agentic development across Amex Technology.
- Own the systems you build in production, including reliability, latency, cost, and failure modes.
- Work closely with product and design partners; engineers in this role are expected to think in terms of customer outcomes, not just technical execution.
**Technical Environment**
We don’t hire to a narrow checklist, but candidates should be comfortable operating in a modern, enterprise-scale environment with a strong emphasis on agentic AI.**Core engineering stack**
- Languages: Python, Go, TypeScript
- Cloud and infrastructure: AWS and/or GCP, Kubernetes
- APIs and services: REST, gRPC
- Distributed systems: event-driven architectures, including Kafka
**Agentic AI and ML**
- Commercial and open-source LLMs integrated into agentic workflows
- Tooling for agent orchestration, retrieval-augmented generation, vector storage, and evaluation
- Strong schema, validation, and state management practices
**AI-assisted development**
- Fluency with AI-assisted and agentic development workflows for design, implementation, testing, debugging, and refactoring
- Thoughtful use of these tools while maintaining production-quality engineering standards
All systems are built to meet high standards for reliability, security, and auditability, reflecting the responsibility of deploying autonomous AI in a financial services environment.
### Qualifications
**What We’re Looking For**
- 5+ years of software engineering experience, including meaningful production experience with LLMs or applied ML systems.
- A track record of shipping AI-powered or agentic systems that real users depend on.
- Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.
- Hands-on experience with modern LLM tooling and agentic patterns and architectures.
- Fluency with AI-assisted and agentic development workflows.
- Strong sense of ownership and sound technical judgment.
- Comfort operating with ambiguity and turning it into shipped reliable product.
- A strong product mindset and customer orientation.
**Preferred Qualifications**
- Experience building agentic systems in fintech or other regulated industries.
- Experience as a founding engineer or early technical contributor in high-growth environments.
- Demonstrated ability to ship technically complex systems in regulated contexts that customers actively rely on.
- Meaningful open-source contributions, particularly in AI or developer tooling.
Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain positions.
Key Responsibilities
- Design, build, and ship LLM-powered and agentic product features for financial management.
- Build agentic AI systems that reason over context, invoke tools, and recover from failures.
- Architect and implement production-grade RAG pipelines over sensitive financial data.
- Contribute to shared AI infrastructure including LLM services and agent orchestration frameworks.
- Own systems in production regarding reliability, latency, cost, and failure modes.
- Collaborate with product and design partners to focus on customer outcomes.
Skills Required
PythonGoTypeScriptAWSGCPKubernetesRESTgRPCKafkaLLMsAgentic AIRAGVector storageAI-assisted development workflowsOwnershipTechnical judgmentComfort with ambiguityProduct mindsetCustomer orientationFintech experienceRegulated industry experienceOpen-source contributionsFounding engineer mindsetTechnical complexity handling
Benefits
- Bonus
- Benefits
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