Seoul, South Korea Role overview
About this role
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
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
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