Staff AI Engineering

As a Staff Data 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. This is an individual contributor, hands-on, deeply technical role with broad architectural ownership and high organizational impact;    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. 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.

Technical Environment We don’t hire to a narrow checklist, but candidates   should be comfortable operating in a modern, enterprise-scale engineering environment with a strong emphasis on agentic AI. Core engineering stack Languages: Python, Go, TypeScript

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

Orchestration Frameworks: LangGraph , LangChain , AirFlow , etc

Agentic AI and ML Integration of commercial and open-source LLMs into agentic workflows

Agent and orchestration frameworks such as LangChain , LlamaIndex , 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 TensorFlow

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

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