Forward Deployed Engineer, Forward Deployment Engineering

A Forward Deployed Engineer II (FDE II) embeds directly inside a strategic enterprise customer to independently design, build, deploy, and run AI-powered production systems alongside the customer's engineering team. FDE IIs write production-grade software and own delivery of complete AI workstreams end-to-end - from requirements gathering through production deployment - combining the technical rigor of an AWS SDE with the urgency and ownership required to deliver measurable customer business outcomes.

FDE IIs are autonomous contributors. They deliver working features spanning the full software lifecycle. They design cohesive implementations for ambiguous problems, making design trade-offs with appropriate guidance. They take on projects where the business problem is understood but implementations are not fully fleshed out, balancing constraints and limiting short-term workarounds. They coach others on producing high-quality code and train new team members.

Key job responsibilities

Embed within customer engineering teams. Work with customers, stakeholders, and peers to understand the business and customer value of the systems you build. Understand the customer's business processes, technical architecture, and operational constraints. Translate customer requirements into technical designs for AI-enabled production systems within your workstream. Requires 30-50% travel.

Build production AI applications. Design and develop production-grade software powering AI and agentic workflows - retrieval pipelines, workflow automation, API orchestration layers, data integration. Solve difficult problems with visible risks or roadblocks, bringing clarity and identifying simple designs for solutions. Integrate foundation models, customer data sources, and existing applications into cohesive AI experiences. Optimize for latency, reliability, and cost.

Own production for your workstream. Be a significant contributor to the full software development lifecycle including scoping, design, code, testing, deployment, operations, and maintenance. Troubleshoot production incidents across AI models, distributed systems, and application services. Ensure root causes of operational issues are identified and resolved. Implement monitoring, evaluations, guardrails, and CI/CD that keep AI systems healthy. Don't settle for the status quo - routinely identify and execute on opportunities to improve operations.

Mentor and uplift. Actively mentors and trains new team members on how systems are constructed, operated, and fit into the bigger picture. Coach others on producing high-quality code through mechanisms such as code review. Be active in the code review process, providing meaningful feedback to others.

Accelerate customer adoption. Identify opportunities to expand AI adoption within your customer engagement. Codify reusable patterns and accelerators that benefit future customer deployments and feed back into AWS services. Make enhancements that improve your team's software and processes.

About the team

ABOUT AWS:

Diverse Experiences

Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS

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Basic qualifications

- 5+ years of non-internship professional software development experience

- 5+ years of programming with at least one software programming language experience

- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience

- Experience as a mentor, tech lead or leading an engineering team

- Experience communicating technical concepts to non-technical audiences

- Experience leading agentic and spec-driven development at production scale (developing AI agents a plus)

- Experience with AI tools: eval frameworks, agent tooling, RAG pipelines, and prompt engineering

Preferred qualifications

- Bachelor's degree in computer science or equivalent

- Experience with AWS services

- Experience building or deploying AI/ML applications at enterprise production scale

- Background as a founder, engineering lead, or startup builder with high ownership and urgency

- Experience architecting and delivering complex, multi-component systems in customer production environments

- Experience with React, TypeScript, Python, and/or Go

- Experience leading customer-facing technical projects or managing external stakeholder relationships

- 3+ years of experience working in an Agile, startup, or rapidly scaling environment

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually