Senior AI Engineer - Enterprise Architecture
Kabbage
Phoenix, AZ · Posted September 28, 2026
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Where Phoenix, AZ ranks
Where Phoenix, AZ placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #3Best cities for government jobs185 openings · of 26
- #3Best all-round cities for remote workers in the Southwest64 / 100 · of 15
- #4Cities with the most jobs that do not need a four-year degree in the Southwest265 jobs · of 38
- #4Best cities for software and engineering jobs in the Southwest692 openings · of 33
- #4Cities hosting the most business conferences in the Southwest31 conferences · of 16
- #5Best cities for manufacturing and industrial jobs505 openings · of 100
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
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How AI is used in this kind of work
Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
At American Express, AI is reshaping the future of commerce and redefining the experiences our commercial customers and card members expect. Within Amex Technology, we are building platforms, products, and governance that enable agentic AI systems to operate responsibly and at scale across the enterprise.
Our focus is on agentic AI development: designing intelligent, adaptive systems that can plan, reason, and act across complex workflows with appropriate levels of autonomy. These systems power autonomous workflows, decision support, and customer-facing experiences—while meeting the high standards for security, explainability, reliability, and compliance required in financial services.
We partner closely with product, design, and business teams to deliver agentic capabilities that reduce operational friction, improve decision-making, and transform how customers interact, transact, and grow.
The Role
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.
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.