Forward Deployed Engineer, AWS Forward Deployed Engineering

Amazon is hiring a Forward Deployed Engineer, AWS Forward Deployed Engineering in London, United Kingdom. Level rates it ; you can apply on Level.

AI in this role

prompt-engineeringragai-agents

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.

A day in the life
You start your morning reviewing deployment metrics from a recent release, then join a design review where you help shape the architecture for an upcoming feature. After lunch, you pair with a teammate on a tricky integration problem, walking through trade-offs together before settling on a clean approach. Later, you onboard a new team member by guiding them through how your services are constructed and operated. Your work balances building new capabilities with strengthening the foundations that keep your systems running reliably.

10047

Basic qualifications

- Experience in professional, non-internship software development
- 3+ years of non-internship professional software development experience
- 2+ years of experience working in an Agile, startup, or rapidly scaling environment
- Experience communicating technical concepts to both technical and non-technical audiences
- Degree in Computer Science or related field, or equivalent professional 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

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.

How we rate this

Forward Deployed Engineer, AWS Forward Deployed Engineering at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Forward Deployed Engineer, AWS Forward Deployed Engineering is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in GB, London.
The job was posted on October 12, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGAI agents

Also common in forward deployed engineer jobs at this level

LLM JavaScript Azure Google Cloud MLOps Spark

Pay

Typical forward deployed engineer job: $182k

This posting doesn't list pay. Use the typical forward deployed engineer figure when pay comes up. See forward deployed engineer jobs

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, and AI agents. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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