Software Development Engineer, AWS Forward Deployed Engineering

Amazon is hiring a Software Development Engineer, AWS Forward Deployed Engineering in Seoul, South Korea. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this forward deployed engineer role Builds AI ●●●●: the job is building AI systems.
The posting mentions prompt engineering, RAG and AI agents among its tools and skills.
Level classes it as a junior role.
Amazon has 20,000+ other open roles on Level.
Posted in the last few days.

AI in this role

prompt-engineeringragai-agents

A Forward Deployed Engineer I embeds directly inside a strategic enterprise customer alongside senior FDEs to help design, build, and deploy AI-powered production systems. FDE Is write production-grade code under the guidance of senior engineers, contributing software components to AI systems that deliver measurable customer business outcomes.
FDE Is are early in their forward-deployment career. They take well-defined tasks within larger AI workstreams and deliver high-quality, well-tested code that goes to production. They learn rapidly from customer environments, constantly absorbing new techniques from senior FDEs. They operate with regular checkpoints and escalate when blocked, progressively taking on more difficult work as they demonstrate competence.

Key job responsibilities
•Embed within customer engineering teams. Work alongside senior FDEs and customer engineers to understand the customer's technical architecture and business context. Execute well-defined tasks within larger AI-enabled production systems. Requires 30–50% travel.
•Build production AI application components. Develop and test production-grade software components — retrieval pipeline modules, workflow automation steps, API integrations, data connectors — under the technical direction of senior FDEs. Write clean, well-tested code that integrates into larger AI and agentic workflow systems. Solve straightforward software problems with visible risks or roadblocks.
•Contribute to production operations. Participate in the full software development lifecycle: development, testing, deployment, operations, and documentation. Assist with production incident triage and operational runbooks. Implement testing, CI/CD pipelines, and observability instrumentation. Identify and resolve root causes of operational issues.
•Learn and grow rapidly. Actively absorb knowledge about customer domains, AI/ML technologies, and AWS services. Seek feedback from senior engineers and apply it immediately. Demonstrate good judgment about when to work independently and when to escalate.
•Contribute to reusable patterns. Identify opportunities to codify recurring solutions into reusable code libraries, templates, or documentation that benefit future customer deployments.

#auta-kr

Basic qualifications

- Bachelor's degree or equivalent
- Bachelor's degree or higher in Computer Science or a related field, or equivalent professional experience, completed between February 2025 and February 2027
- Experience working in customer-facing or production environments
- Strong business communication skills and high attention to detail
- Business-level proficiency in both Korean and English
- Legal authorization to work in Korea (Visa sponsorship is not available)

Preferred qualifications

- 1+ years of non-internship professional software development experience
- 1+ years of experience working in an Agile, startup, or fast-scaling environment
- Exposure to agentic and spec-driven development (developing AI agents a plus)
- Familiarity with AI tools: eval frameworks, agent tooling, RAG pipelines, or prompt engineering
- Exposure to building or deploying AI/ML applications
- Prior experience with Python, React, TypeScript, and/or Go[SA4.1]
- Experience with full software development lifecycle — coding standards, code reviews, source control, build processes, testing, and operations
- Strong written and verbal communication skills; comfortable working in customer-facing environments

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

Software Development Engineer, AWS Forward Deployed Engineering at Amazon rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● 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. Read the description and count the AI tools, models and workflows it names.

Key facts

Software Development Engineer, AWS Forward Deployed Engineering is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in KR, Seoul.
The job was posted on November 13, 2026.
Seniority: junior.
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 Generative AI Machine learning Google Cloud Azure Fine-tuning

Pay

Typical forward deployed engineer job: $180k

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?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

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.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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