Senior AI Engineer II - Forward Deployment Engineer - Enterprise AI Platforms

American Express•Sunnyvale, CA

7d•$123,000 - $215,250

About The Position

The Forward Deployed AI Engineer partners with business units, product teams, and engineering organizations to identify high-value opportunities, translate business challenges into measurable value propositions, and build trusted, secure, responsible AI solutions using generative AI, agentic systems, and intelligent automation. The role takes opportunities from discovery and demonstration through proof of value, production scaling, adoption, and transition to long-term ownership, with measurable outcomes and enterprise requirements for security, reliability, governance, and responsible AI in view. This is a hands-on engineering role with significant stakeholder engagement. The engineer works directly with users and engineering teams, communicates across technical and seniority levels, challenges assumptions, analyzes workflows as systems, and connects near-term solutions to longer-term transformation. Candidates may have backgrounds in mobile, web, backend, distributed systems, or workflow platforms; the key is understanding systems end to end and turning direction into working software. The role also helps generalize successful engagement patterns into reusable enterprise capabilities, supports adoption of AI-enabled workflows, and contributes lessons to the enterprise AI platform and product roadmap. Occasional travel may be required for workshops or key delivery milestones; frequent travel is not expected. Positions may be based near selected American Express offices to support regional business and product partnerships. The working arrangement may be onsite, hybrid, or virtual depending on the role and business need.

Requirements

At least 5 years of experience delivering software, technical solutions, or digital products in an engineering, architecture, or technical consulting capacity.
Demonstrated ability to take an ambiguous business or user problem through discovery, implementation, and measurable validation.
Experience using coding agents in a structured engineering workflow, including specification-driven development, context management, iterative implementation, and reusable knowledge repositories.
Software engineering fluency and ability to contribute directly to applications, integrations, services, or technical prototypes.
Experience in at least one relevant domain, such as mobile, web, backend services, APIs, distributed systems, platform engineering, workflow orchestration, or cloud-native development.
Ability to reason about systems end to end, identify constraints and leverage points, and connect technical decisions to business outcomes.
Strong communication and stakeholder-partnership skills, including explaining technical concepts, constructively challenging existing approaches, and influencing without direct authority.
Ability to define a longer-term direction and sequence incremental solutions toward it.
Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
Must be eligible to work in the United States for American Express; the company will not pursue visa sponsorship.

Nice To Haves

Experience building or deploying solutions powered by language models, agentic systems, or AI-enabled process flows.
Experience with retrieval-augmented generation, vector databases, tool calling, model context protocols, knowledge retrieval, or workflow technologies such as Temporal, LangGraph, LangChain, or LlamaIndex.
Experience designing human-in-the-loop controls and operational safeguards, with knowledge of AI evaluation, observability, and responsible AI.
Experience supporting technology adoption or operating-model transformation, particularly in financial services or another regulated industry.

Responsibilities

Build trusted relationships and understand business priorities, user needs, operational workflows, and sources of friction.
Challenge existing assumptions, map processes as systems, and identify technical, operational, and organizational opportunities for improvement.
Lead discovery sessions to define use cases, value propositions, measurable success criteria, and solution direction.
Assess opportunities based on business value, technical feasibility, user impact, risk, and adoption readiness.
Define a longer-term vision and identify small, useful interventions that validate opportunities while preserving a path to broader transformation.
Design, build, and deploy generative AI, agentic AI, and intelligent automation solutions using approved enterprise platform capabilities.
Develop demonstrations and proofs of value that test assumptions and measure business impact.
Take solutions through prototyping, production scaling, adoption, and transition to long-term ownership.
Build agents and AI-enabled workflows that interact with enterprise APIs, knowledge sources, data platforms, applications, code, and business processes.
Incorporate appropriate human input, approval, escalation, and fallback mechanisms.
Work alongside engineering teams to produce software and apply production-ready architecture, testing, deployment, and operational practices.
Use experimentation selectively to reduce uncertainty while balancing speed with security, reliability, maintainability, and governance.
Use coding agents and AI-assisted engineering techniques to accelerate discovery, implementation, testing, documentation, and iteration.
Apply specification-driven development, context management, iterative planning, and structured knowledge repositories.
Evaluate agent-generated code and technical outputs for correctness, security, maintainability, and architectural alignment.
Identify opportunities for AI-enabled development practices to improve engineering throughput without compromising operational standards.
Generalize engagement patterns and components for broader use.
Partner with platform and product teams to turn successful prototypes into reusable features, accelerators, reference architectures, and paved-road implementation patterns.
Capture deployment lessons and influence the enterprise AI platform and product roadmap.
Help teams adopt AI-enabled workflows and transition solutions into sustainable operating models.
Develop evaluation approaches for solution quality, task completion, business outcomes, user experience, latency, cost, and reliability.
Identify and address failure modes through testing, monitoring, safeguards, and iterative improvement.
Ensure solutions meet American Express requirements for security, privacy, risk management, responsible AI, and regulatory compliance.
Establish controls for model access, enterprise data, tool use, human oversight, and production operations.
Communicate technical concepts, tradeoffs, risks, and recommendations to audiences with varying technical familiarity and seniority.
Influence decisions and drive alignment across business, product, engineering, risk, and platform teams without direct reporting authority.
Maintain stakeholder relationships throughout discovery, delivery, adoption, and transition, and mentor partner teams on AI solution delivery.

Benefits

Competitive base salaries
Bonus incentives
6% company match on retirement savings plan
Free financial coaching and financial well-being support
Comprehensive medical, dental, vision, life insurance, and disability benefits
Flexible working model with hybrid, onsite, or virtual arrangements depending on role and business need
20+ weeks of paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption, or surrogacy
Free access to global onsite wellness centers staffed with nurses and doctors, depending on location
Free and confidential counseling support through the Healthy Minds program
Career development and training opportunities