Staff AI Engineer - Enterprise Architecture

Staff AI Engineer - Enterprise Architecture

Phoenix, AZ, United States

New York, NY, United States

(Hybrid)

** Job Description*
* 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 Staff Software Engineer - Agentic AI, you will operate as a senior individual contributor within Amex Technology, helping define how agentic AI systems are designed, built, and operated across the company.

You will work at the intersection of agentic system architecture and hands-on execution: designing core frameworks, writing production code, reviewing critical designs, and guiding teams through complex technical decisions. This role does not include people management; your impact comes from technical leadership, sound judgment, and the ability to turn ambiguity into reliable, scalable agentic systems.

You will work closely with Product and UX partners to shape a shared vision for agentic AI experiences. While product teams own prioritization, Staff engineers are expected to actively influence _what_ gets built and _how_ agentic systems come together across teams.

We are primarily looking for senior individual contributors; however, as the team grows, you will take on increasing responsibility for technical leadership and people development within the agentic AI space. Mentoring, developing and managing direct reports may be in scope for some of our opportunities.

** Responsibilities*
* ** What You'll Do*
* + Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design.

+ Design, build, and operate production-grade agentic AI systems used across multiple products.

+ Own and evolve shared agentic AI capabilities, including:

+ Agent frameworks and orchestration layers

+ Planning, tool use, and memory strategies

+ Retrieval and grounding (RAG) pipelines

+ LLM infrastructure, inference, and model gateways

+ Evaluation, observability, and safety tooling for autonomous systems

+ Lead technical design reviews and help teams navigate tradeoffs involving autonomy, safety, reliability, scalability, and cost.

+ Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to production.

+ Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise-ready improvements.

+ Mentor senior engineers and raise the technical bar for agentic AI development through example and influence.
** Core engineering stack*
* +

Languages:

Python, Go, Type Script

+ APIs and RPC: REST, gRPC (and in some areas tRPC)

+ Cloud and infrastructure: AWS and/or GCP, Kubernetes

+ Distributed systems: event-driven architectures, including Kafka
** Agentic AI and ML*
* + Integration of commercial and open-source LLMs into agentic workflows

+ Agent and orchestration frameworks such as Lang Chain, Llama Index, Semantic Kernel, or CrewAI, with strong judgment about when to use frameworks versus building lighter-weight primitives

+ Model-level work using PyTorch and the Hugging Face ecosystem (embeddings, fine-tuning, inference tooling), with some exposure to Tensor Flow

+ Strong schema, validation, and state management practices using tools such as Pydantic (Python) and Zod (Type Script)

+ Across all systems, we emphasize evaluation, observability, safety, and reliability, reflecting the responsibility of deploying autonomous AI in a regulated, customer-facing environment.

** Qualifications*
* + +10 years of software engineering expereince, including deep, hands-on experience delivering agentic or LLM-powered systems to production

+ Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products. +10 years of software engineering expereince, including deep, hands-on experience delivering agentic or LLM-powered systems to production

+ Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.

+ Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.

+ Fluency with AI-assisted and agentic development workflows.

+ Comfort operating in ambiguous problem spaces and translating them into shipped, reliable…