{"id":1656993,"url":"https://alion.io/job/american-express-sr-ai-engineer-ii-2","title":"Sr AI Engineer II","company":{"id":2209,"name":"American Express","domain":"americanexpress.com","url":"https://alion.io/company/american-express","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":100,"open_postings":50,"ghost_share":0,"stale_share":0.06,"repost_share":0.2,"time_to_fill_p50_days":8,"computed_at":"2026-10-21T05:46:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sunrise, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":126000,"max_usd":241000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1268},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Function Calling","optional":false},{"name":"GitOps","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Least Privilege","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"TypeScript","optional":false},{"name":"A2A","optional":true},{"name":"Embeddings","optional":true},{"name":"Google ADK","optional":true},{"name":"LangChain","optional":true},{"name":"Langfuse","optional":true},{"name":"LangGraph","optional":true},{"name":"LLM","optional":true},{"name":"OpenAI Agents SDK","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"Semantic Kernel","optional":true},{"name":"Threat Modeling","optional":true}],"status":"live","first_seen_at":"2026-10-01T16:21:32Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-21T20:42:59Z","board_verified":true,"closed_at":null,"days_open":20,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":19},"description":"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.\nThe 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.\nAt 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.\nOur 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.\nWe 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.\nThe Enterprise Data & AI Team creates the platforms, products, and governance that power enterprise AI. Our team enables rapid experimentation, seamless deployment, and responsible operation of AI systems at scale - delivering trusted, compliant, and high-performance AI solutions that drive meaningful business outcomes, partnering with stakeholders to support use cases from inception to implementation.\nAmerican Express is building an enterprise-grade Agentic AI Platform designed to enable teams to safely build, deploy, operate, discover, govern, and continuously improve AI agents at scale.\nWe are looking for a Senior AI Engineer to help design and build the foundational platform capabilities that power agentic AI across the enterprise. This is a hands-on engineering role at the intersection of AI systems, distributed platforms, cloud infrastructure, developer tooling, and enterprise governance.\nThis role is ideal for an engineer who wants to go beyond building individual AI applications and instead build the platform and infrastructure that enables hundreds of teams and AI agents to operate safely and reliably at enterprise scale.\nWhat You'll Build\nYou will contribute to the architecture and implementation of capabilities across the Agentic AI Platform, including:\nAgent Runtime & Execution\nDesign and build scalable agent runtime infrastructure using Kubernetes and cloud-native technologies.\nDevelop runtime abstractions that allow agents to execute across internally managed sandboxed environments and third-party AI platforms.\nBuild capabilities for agent orchestration, tool execution, state and context management, memory, asynchronous workloads, event-driven execution, and multi-agent workflows.\nEnterprise Agent Control Plane\nBuild a unified control plane for managing agents across heterogeneous execution environments and AI providers.\nDevelop APIs and services for agent registration, configuration, deployment, versioning, lifecycle management, policy enforcement, and runtime management.\nCreate abstractions that reduce provider-specific complexity while preserving access to differentiated capabilities across AI ecosystems.\nAgent Governance & Security\nEngineer platform-level controls for enterprise AI governance, including agent identity, authentication and authorization, tool permissions, policy enforcement, data boundaries, auditability, and lifecycle controls.\nBuild mechanisms for governing models, prompts, tools, MCP servers, knowledge sources, agent-to-agent interactions, and external integrations.\nPartner with security, risk, privacy, and governance teams to translate enterprise requirements into scalable technical controls.\nAgent Discovery & Ecosystem\nBuild registries and catalogs that allow developers and AI systems to discover reusable agents, tools, skills, prompts, models, knowledge sources, and other platform capabilities.\nDevelop metadata, ownership, versioning, dependency, certification, and discovery mechanisms that enable a healthy enterprise agent ecosystem.\nAgent Observability\nBuild end-to-end telemetry for agent execution, including traces, events, model interactions, tool calls, latency, token consumption, cost, failures, policy decisions, and quality signals.\nDevelop capabilities that make complex and multi-agent workflows explainable and debuggable.\nEnable platform and application teams to understand agent behavior across multiple models, runtimes, tools, and external systems.\nEvaluation & Continuous Learning\nDevelop evaluation frameworks for measuring agent quality, reliability, safety, and task performance.\nBuild automated evaluation pipelines incorporating offline evaluations, production signals, human feedback, regression testing, and experimentation.\nHelp create continuous learning loops that turn production telemetry and feedback into actionable improvements to agents, prompts, tools, models, and platform capabilities.\nDeveloper Experience\nBuild SDKs, APIs, CLIs, templates, local development environments, and self-service workflows that make agent development simple and productive.\nCreate opinionated paved roads that allow developers to move quickly while automatically incorporating enterprise security, governance, observability, and operational standards.\nAI CI/CD & Platform Engineering\nBuild CI/CD capabilities specifically designed for AI agents, including automated evaluation, policy validation, security checks, artifact/version management, deployment, promotion, rollback, and release controls.\nDesign GitOps and infrastructure-as-code patterns for deploying and managing agent workloads.\nHelp establish engineering standards for taking agents from experimentation to production safely and repeatedly.\n Design and implement highly scalable components of the enterprise Agentic AI Platform.\nOwn complex technical problems from architecture through production implementation and operation.\nBuild distributed services and APIs supporting agent execution and lifecycle management.\nDevelop integrations with major AI/model ecosystems and managed agent platforms.\nEstablish common abstractions across models, agents, tools, runtimes, and providers.\nDesign systems for agent identity, permissions, policy enforcement, and governance.\nBuild observability, evaluation, and experimentation capabilities for production AI systems.\nDevelop SDKs, tooling, and automation that dramatically improve developer productivity.\nDesign reliable CI/CD and release processes for AI agents and related artifacts.\nEstablish patterns for resilience, scalability, performance, security, and cost efficiency.\nEvaluate emerging agent frameworks, protocols, models, and infrastructure technologies and determine where they fit within the enterprise platform.\nPartner with product, architecture, security, risk, infrastructure, and application engineering teams.\n Minimum Qualifications\nStrong software engineering experience building production systems using languages such as Python, Java, Go, or TypeScript.\nStrong understanding of Generative AI, LLMs, agent architectures, tool/function calling, retrieval, context management, and agent orchestration.\nExperience building production applications or platforms using major model providers or AI platforms.\nExperience with Kubernetes, containers, microservices, distributed systems, and cloud-native architecture.\nExperience designing production APIs and event-driven or asynchronous systems.\nStrong understanding of modern cloud infrastructure and infrastructure-as-code practices.\nExperience with CI/CD, automated testing, production observability, and software delivery practices.\nStrong understanding of security fundamentals including identity, authentication, authorization, secrets, and least-privilege access.\nAbility to navigate ambiguous technical problems and turn emerging technologies into reliable production systems.\nStrong communication skills and ability to collaborate across engineering, architecture, product, security, and governance organizations.\nCandidates are required to have a bachelor’s degree\nPreferred Qualifications\nExperience in several of the following areas is highly desirable:\nAgent frameworks and orchestration technologies such as LangGraph, Semantic Kernel, Google ADK, OpenAI Agents SDK, or similar frameworks.\n Model Context Protocol (MCP) and emerging agent interoperability protocols like A2A.\nMulti-agent systems and agent-to-agent communication patterns.\nKubernetes operators, controllers, service meshes, or sophisticated Kubernetes platform engineering.\nAgent/model gateways and intelligent model routing.\nVector databases, retrieval systems, embeddings, and enterprise knowledge architectures.\nLLM and agent evaluation frameworks, LLM-as-judge techniques, human feedback systems, experimentation, and quality measurement.\nAI observability, distributed tracing, OpenTelemetry, Langfuse and production monitoring.\nExperience with Evals\nPolicy engines and policy-as-code.\nAI security, prompt injection defenses, tool security, data-loss prevention, and AI-specific threat modeling.\nPlatform engineering, internal developer platforms, developer portals, and enterprise service catalogs.\nLarge-scale distributed systems operating in highly regulated environments.\nWhat Success Looks Like\nYou will help make it possible for developers across American Express to move from an agent idea to a governed production deployment through a consistent, self-service platform.\nSuccessful platform capabilities will make the secure and reliable path the easiest path: developers should be able to build once and operate agents across multiple AI ecosystems while receiving governance, identity, observability, evaluation, deployment, and operational capabilities by default.\nYou will play a key role in establishing the engineering foundations for an enterprise ecosystem in which AI agents can be built, discovered, trusted, governed, observed, evaluated, deployed, and continuously improved at scale.\nDepending 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.","description_format":"text","description_chars":10984,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Cards & Card Issuing","Payment Processing & 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