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Prompt Software Engineer

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Onsite

Prompt Software Engineer

Mitr Phol Sugar Corp., Ltd.

Prompt Software Engineer

Skills

Google Cloud PlatformSQL QueriesNextReactNodePythonGolangPostgreSQLMySQLAIAWSNo-code Automationsn8nJavascriptAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

THB 420,000 – THB 600,000 / year

Location:

Bangkok, Thailand

Work mode:

Onsite

Published on:

11 August 2026

What they need


Position : Prompt Software Engineer (GenAI & Automation Specialist)

บริษัท ยูไนเต็ด แสตนดาร์ด เทอร์มินัล จำกัด (มหาชน)

Job Overview

We are seeking a forward-thinking and highly skilled Prompt Software Engineer to join our development team. In this role, you will not just write traditional code, but fundamentally change how software is built by leveraging cutting-edge Generative AI models (such as Anthropic Claude, OpenAI GPT) to architect, develop, and deploy full-stack applications.

You will be responsible for building end-to-end software solutions, with a heavy emphasis on robust Backend architectures, API development/integration, and complex AI automation workflows using n8n. If you are a developer who has mastered the art of AI-assisted engineering and workflow automation, we want you on our team.

Key Responsibilities

  • AI-Driven Development: Architect and build full-stack applications (Frontend, Backend, and APIs) by effectively directing and collaborating with Large Language Models (LLMs) like Claude.
  • Backend & API First Architecture: Design, develop, and maintain scalable, secure, and high-performance APIs and backend systems that serve as the backbone of our applications.
  • Workflow Automation: Build, optimize, and manage complex, multi-step AI automation pipelines and integrations using n8n.
  • Prompt Engineering: Design, test, and refine advanced system prompts and agentic workflows to ensure deterministic, reliable, and high-quality outputs from GenAI models.
  • Integration: Seamlessly connect Frontend interfaces with Backend services and third-party AI APIs.
  • Continuous Optimization: Monitor AI token usage, latency, and costs, while continuously refactoring code generated by AI to meet production-grade standards.

Job Qualifications

Technical Skills & Experience

  • Proven Experience: 2+ years of experience in software development, with a strong portfolio of projects built leveraging Generative AI tools.
  • GenAI Expertise: Deep understanding of LLM capabilities, limitations, and advanced prompt engineering techniques (e.g., Chain-of-Thought, Few-Shot prompting, Retrieval-Augmented Generation / RAG).
  • Automation Platforms: Hands-on, practical experience building production-grade workflows in n8n (experience with custom JavaScript/Python nodes within n8n is highly preferred).
  • Backend & API Development: Strong proficiency in backend technologies (e.g., Node.js, Python, Go) and expert-level knowledge in designing and consuming RESTful APIs and Webhooks.
  • Frontend Basics: Good understanding of modern frontend frameworks (e.g., React, Vue, or Next.js) to ensure smooth full-stack integration.
  • Database Knowledge: Experience working with SQL (PostgreSQL, MySQL) and NoSQL databases, as well as Vector Databases (e.g., Pinecone, Chroma) for AI context storage.

Soft Skills & Mindset

  • AI-Native Mindset: An obsessive curiosity about the evolving GenAI landscape and a passion for automating repetitive tasks.
  • Problem-Solving: Exceptional debugging and critical thinking skills—knowing when to rely on AI and when to apply traditional engineering principles.
  • Adaptability: Ability to thrive in a fast-paced environment where tools and AI models update frequently.
  • Communication: Strong technical communication skills to document workflows, API specifications, and system architectures clearly.

Preferred Qualifications (Nice to Have)

  • Experience with AI agent frameworks (e.g., LangChain, CrewAI, AutoGen).
  • Familiarity with DevOps, CI/CD pipelines, and cloud platforms (AWS, GCP, or Azure).
  • Experience with token optimization and cost-management strategies for LLM deployment.

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