Staff AI Engineering
for sections present: About the role (maybe from description?), Responsibilities, Qualifications, Technical Environment? The rules: Use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Use - for any list of duties/requirements/benefits, and
for prose. Do NOT repeat the job title as a heading. Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it. Preserve ALL substantive information; do NOT invent or summarize away detail. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. IMPORTANT: include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text (e.g. "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. Prefer a few substantive sections over many thin ones.
We need to parse the job description.
The content includes:
- Intro paragraph about American Express culture, etc. That's "About the role" maybe? Actually "About the role" could be the introductory description. We'll treat that as "About the role".
- Then "Responsibilities" section with bullet points.
- Then "Technical Environment" (maybe "Technical Environment" is not a standard heading but we can treat as "Technical Environment" maybe as a subsection under "Qualifications"? But we can create a heading "Technical Environment" if content is specific. The rules only list certain headings but we can use others? It says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but suggests those examples. Probably we should stick to those. "Technical Environment" could be part of "Qualifications" or "Skills". But we have a "Qualifications" section later. The "Technical Environment" describes stack, languages, etc. That could be considered "Skills" or "Requirements". The rules mention "Requirements" as a possible heading. We could put technical environment under "Requirements" or "Skills". Since we have a "Qualifications" section with bullet points of qualifications, we could also have a "Skills" section for technical stack. However the instruction: Prefer a few substantive sections over many thin ones. So maybe combine technical environment into "Qualifications" or "Requirements". But we already have a "Qualifications" section with bullet points of qualifications (10+ years experience etc). The technical environment is more about required skills. Could be "Requirements". Let's decide: We'll have sections: About the role, Responsibilities, Qualifications (including both experience qualifications and technical skills). Could also split into "Qualifications" and "Skills". But to avoid many thin sections, we can combine.
We need to preserve all substantive information. So we need to include the bullet points under Responsibilities, the bullet points under Qualifications (including preferred qualifications), and the technical environment details.
We must not include boilerplate like "At American Express, our culture is built..." That's substantive? It's about company culture, but it's part of job description. It's not boilerplate like EEO. It's okay to keep as part of About the role.
We must not include duplicated lines. There's some duplication: "LangGraph , LangChain , AirFlow , etc" appears twice? Actually appears in Technical Environment: "Orchestration Frameworks: LangGraph , LangChain , AirFlow , etc". Then later "Agent and orchestration frameworks such as LangChain , LlamaIndex , Semantic Kernel, or CrewAI". Slightly different but similar. We'll keep both as they are distinct.
We must not include application instructions. There's none.
We must not include cookie/navigation/legal/EEO etc. Not present.
Now produce HTML.
Structure:
About the role
... (intro paragraphs up to before Responsibilities)
Then Responsibilities
- ... each bullet
Then Qualifications
We need to include both the required qualifications bullet list and preferred qualifications bullet list, plus technical environment details. Could embed technical environment as a or
. Since it's a list of technologies, we can use .
We need to preserve all substantive information: The qualifications bullet list:
- 10+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure
- Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
- 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 autonomous systems.
- Ability to influence technical direction and align teams without formal authority.
- Experience in workflow engines, async processing, queues, and streaming systems.
Preferred qualifications:
- Experience building agentic systems in fintech or other regulated industries.
- Experience as a founding engineer or early technical leader in AI-driven products.
- Demonstrated success delivering technically complex autonomous systems that customers actively rely on.
- Meaningful contributions to open-source AI or agentic frameworks.
- Familiarity with fine-tuning, model optimization and inference pipelines is a plus
Technical Environment bullet list:
- 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.
We need to format as list items. Could break into sub-items but we can keep as plain text within - . Might be long but okay.
We must not invent or summarize away detail. So we need to keep the exact phrasing.
Now produce HTML.
Check for any filler like "commensurate with experience" - none.
Now output only HTML fragment.
Let's craft.
We need to ensure we don't include any markdown fences.
We'll output:
About the role
At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. Joining Amex Tech means discovering and shaping your contribution to something big. Here, you can work alongside talented tech teams and build a unique career with the Powerful Backing of American Express. With a range of opportunities to work with the latest technologies, and a commitment to back the broader engineering community through open source, our mission is to power your success. Because Amex Tech is powered by our technology, our culture, and our colleagues. The Technology organization enables and accelerates the company’s growth strategies, delivering global capabilities and services in support of Amex’s customers and colleagues, while maintaining 24/7 servicing and availability to ensure an uninterrupted, high-quality customer experience. Technology provides the foundation for everything we do in the company while driving differentiation through building and leveraging innovative technology and data insights. 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.
Responsibilities
- 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.
Qualifications
- 10+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure
- Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
- 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 autonomous systems.
- Ability to influence technical direction and align teams without formal authority.
- Experience in workflow engines, async processing, queues, and streaming systems.
- Preferred Qualifications:
- Experience building agentic systems in fintech or other regulated industries.
- Experience as a founding engineer or early technical leader in AI-driven products.
- Demonstrated success delivering technically complex autonomous systems that customers actively rely on.
- Meaningful contributions to open-source AI or agentic frameworks.
- Familiarity with fine-tuning, model optimization and inference pipelines is a plus
But we also need to include Technical Environment. Could add as another Technical Environment
but not
- for any list of duties/requirements/benefits, and
for prose. Do NOT repeat the job title as a heading. Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it. Preserve ALL substantive information; do NOT invent or summarize away detail. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. IMPORTANT: include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text (e.g. "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. Prefer a few substantive sections over many thin ones. We need to parse the job description. The content includes: - Intro paragraph about American Express culture, etc. That's "About the role" maybe? Actually "About the role" could be the introductory description. We'll treat that as "About the role". - Then "Responsibilities" section with bullet points. - Then "Technical Environment" (maybe "Technical Environment" is not a standard heading but we can treat as "Technical Environment" maybe as a subsection under "Qualifications"? But we can create a heading "Technical Environment" if content is specific. The rules only list certain headings but we can use others? It says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but suggests those examples. Probably we should stick to those. "Technical Environment" could be part of "Qualifications" or "Skills". But we have a "Qualifications" section later. The "Technical Environment" describes stack, languages, etc. That could be considered "Skills" or "Requirements". The rules mention "Requirements" as a possible heading. We could put technical environment under "Requirements" or "Skills". Since we have a "Qualifications" section with bullet points of qualifications, we could also have a "Skills" section for technical stack. However the instruction: Prefer a few substantive sections over many thin ones. So maybe combine technical environment into "Qualifications" or "Requirements". But we already have a "Qualifications" section with bullet points of qualifications (10+ years experience etc). The technical environment is more about required skills. Could be "Requirements". Let's decide: We'll have sections: About the role, Responsibilities, Qualifications (including both experience qualifications and technical skills). Could also split into "Qualifications" and "Skills". But to avoid many thin sections, we can combine. We need to preserve all substantive information. So we need to include the bullet points under Responsibilities, the bullet points under Qualifications (including preferred qualifications), and the technical environment details. We must not include boilerplate like "At American Express, our culture is built..." That's substantive? It's about company culture, but it's part of job description. It's not boilerplate like EEO. It's okay to keep as part of About the role. We must not include duplicated lines. There's some duplication: "LangGraph , LangChain , AirFlow , etc" appears twice? Actually appears in Technical Environment: "Orchestration Frameworks: LangGraph , LangChain , AirFlow , etc". Then later "Agent and orchestration frameworks such as LangChain , LlamaIndex , Semantic Kernel, or CrewAI". Slightly different but similar. We'll keep both as they are distinct. We must not include application instructions. There's none. We must not include cookie/navigation/legal/EEO etc. Not present. Now produce HTML. Structure:
About the role
... (intro paragraphs up to before Responsibilities)
ThenResponsibilities
- ... each bullet
Qualifications
We need to include both the required qualifications bullet list and preferred qualifications bullet list, plus technical environment details. Could embed technical environment as aor
- . Since it's a list of technologies, we can use
- . Might be long but okay.
We must not invent or summarize away detail. So we need to keep the exact phrasing.
Now produce HTML.
Check for any filler like "commensurate with experience" - none.
Now output only HTML fragment.
Let's craft.
We need to ensure we don't include any markdown fences.
We'll output:
About the role
At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. Joining Amex Tech means discovering and shaping your contribution to something big. Here, you can work alongside talented tech teams and build a unique career with the Powerful Backing of American Express. With a range of opportunities to work with the latest technologies, and a commitment to back the broader engineering community through open source, our mission is to power your success. Because Amex Tech is powered by our technology, our culture, and our colleagues. The Technology organization enables and accelerates the company’s growth strategies, delivering global capabilities and services in support of Amex’s customers and colleagues, while maintaining 24/7 servicing and availability to ensure an uninterrupted, high-quality customer experience. Technology provides the foundation for everything we do in the company while driving differentiation through building and leveraging innovative technology and data insights. 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.
Responsibilities
- 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.
Qualifications
- 10+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure
- Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
- 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 autonomous systems.
- Ability to influence technical direction and align teams without formal authority.
- Experience in workflow engines, async processing, queues, and streaming systems.
- Preferred Qualifications:
- Experience building agentic systems in fintech or other regulated industries.
- Experience as a founding engineer or early technical leader in AI-driven products.
- Demonstrated success delivering technically complex autonomous systems that customers actively rely on.
- Meaningful contributions to open-source AI or agentic frameworks.
- Familiarity with fine-tuning, model optimization and inference pipelines is a plus
Technical Environment
but not
- .
We need to preserve all substantive information: The qualifications bullet list:
- 10+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure
- Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
- 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 autonomous systems.
- Ability to influence technical direction and align teams without formal authority.
- Experience in workflow engines, async processing, queues, and streaming systems.
Preferred qualifications:
- Experience building agentic systems in fintech or other regulated industries.
- Experience as a founding engineer or early technical leader in AI-driven products.
- Demonstrated success delivering technically complex autonomous systems that customers actively rely on.
- Meaningful contributions to open-source AI or agentic frameworks.
- Familiarity with fine-tuning, model optimization and inference pipelines is a plus
Technical Environment bullet list:
- 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.
We need to format as list items. Could break into sub-items but we can keep as plain text within