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.
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.
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.
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