Forward Deployed Engineer, AWS Forward Deployed 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 well-understood 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.

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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, 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 Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 10047

Basic qualifications

- Experience communicating technical concepts to non-technical audiences

- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience

- Experience with agentic and spec-driven development (developing AI agents a plus)

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

Preferred qualifications

- Experience working in customer production environments

- Experience building or deploying AI/ML applications in production environments

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

- Prior experience with React, TypeScript, Python, and/or Go

- Experience interfacing with customers or leading technical projects with external stakeholders

- Experience working with teams that build and scale end-to-end production systems

- Experience with AWS services

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.