Senior AI Engineer – Global Commercial Services

🔥 12 hours ago

🌲 North Carolina – Remote

🌲 North Carolina – Remote

💵 $123k - $215.3k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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American Express

WebsiteLinkedInAll Job Openings

10,000+ employees

🏦 Banking

💸 Finance

🤝 B2B

Banking • Finance • B2B

American Express is a global financial services company that issues consumer, business, and corporate credit cards, operates payment and merchant services, and offers banking products such as savings accounts, certificates of deposit, and personal loans. It provides rewards and travel programs, corporate and B2B payment solutions, financial education and security services, and extensive cardmember and merchant support.

📋 Description

• Build production agentic AI services end to end, from event trigger through LLM reasoning to persisted, surfaced results • Contribute to the shared agent framework, including orchestration, tool use, structured generation, and observability • Build RAG and embedding pipelines using vector search in the operational database • Implement evaluations for new agent behaviors and use them to gate prompt changes • Build for reliability through failure classification, idempotency, DLQ handling, and safe AI-feature rollouts • Participate in technical design discussions and code reviews, growing toward owning designs • Help onboard engineers onto the AI stack • Work across TypeScript and Go services, gRPC and tRPC APIs, Kafka, SQS, Lambda, EKS on AWS, feature-flagged rollouts, and infrastructure as code

🎯 Requirements

• 4+ years building backend or distributed systems in production • Shipped LLM-powered features, including prompts, retrieval, output handling, and surrounding model-call systems • Strong TypeScript or Go, with willingness to work across both • Solid distributed-systems fundamentals, including queues, event-driven design, and failure modes • Curiosity about what an LLM should decide versus what code should decide • Clear communication across engineering, product, and design • Experience building or maintaining internal platform tooling or frameworks (nice to have) • Experience writing LLM evaluations or working with LLM observability tooling (nice to have) • Experience with durable execution or workflow orchestration engines such as Temporal (nice to have) • AI features shipped in financial services or another regulated industry (nice to have) • Vector search or embedding pipelines in production (nice to have)

🏖️ Benefits

• Bonus • Benefits