Senior AI Engineer – Global Commercial Services

American Express

. Build production agentic AI services end to end, from event trigger through LLM reasoning to persisted, surfaced results .

Posted 9/22/2026full-timeRemote • North Carolina • United StatesSenior💰 $123,000 - $215,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building production-grade AI services, with a strong focus on TypeScript and Go, distributed systems, and LLM-powered features. Capable of contributing to technical design discussions and onboarding engineers while ensuring reliability and observability in AI implementations.

Highest-signal resume keywords

TypeScript DevelopmentGo DevelopmentDistributed Systems FundamentalsLLM-Powered FeaturesWorkflow Orchestration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend DevelopmentEvent-Driven DesignFailure ClassificationIdempotencyVector SearchEmbedding PipelinesLLM EvaluationsDurable ExecutionInfrastructure as CodeObservability Tooling

Soft Skills

Clear CommunicationCuriosity

Tools & Technologies

GRPCTRPCKafkaSQSLambdaEKSTemporal

Industry Keywords

AI FeaturesFinancial ServicesRegulated Industry

Tech Stack

Tools & technologies

AWSDistributed SystemsGRPCKafkaTypeScriptGo

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Bonus
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