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Job Description Low-code AI — building and maintaining internal apps, workflows, and AI agents on the Microsoft ecosystem (Power Apps, Power Automate, Copilot Studio, Azure AI Foundry) Pro-code AI — developing AI agents: RAG pipelines, function calling, Model Context Protocol (MCP), conversation memory, tool-enabled AI agent integrations, agent orchestration frameworks; open-source agent frameworks and harnesses (e.g., LangChain, OpenClaw, Hermes-style agents) Integrate APIs with API Gateway for authentication, authorization, rate limiting, and monitoring. Document and maintain API specifications using OpenAPI/Swagger. Integrate AI services (e.g., Amazon Bedrock, Amazon SageMaker, Azure OpenAI) into enterprise applications. Design and Assist with Retrieval-Augmented Generation (RAG) using enterprise knowledge bases and vector databases, testing retrieval quality, and tuning for accuracy, relevance, and reliability. Integrate AI applications with enterprise systems through REST APIs, SOAP Web Services, Webhooks, and enterprise integration platforms. Build scalable AI inference services and support AI application deployment. Deploy and manage AI applications on AWS Cloud and support Azure AI services when required. Implement containerized deployments using Docker and support CI/CD pipelines including monitoring, performance tracking, version control, observability, and lifecycle management. Apply secure AI development practices and Responsible AI principles, including privacy, governance, and data protection. Contribute to technical documentation, knowledge sharing, and continuous improvement of AI engineering practices. Explore emerging AI technologies, industry trends, foundation models, tools, and frameworks to enhance team capabilities. Qualifications 1–3 years of experience as an AI Engineer, Software Engineer, Backend Engineer, or related field. Strong programming skills in Python (Node.js is a plus). Experience designing and developing RESTful APIs and basic knowledge of SOAP Web Services. Experience developing AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or AI Agents. Experience with Low-Code AI; Power Apps, Power Automate, or Copilot Studio Experience with Data Analytics and Visulization tools, OCR, Document processing, or Web Scraping/Automation (e.g., Playwright) Familiar with AI frameworks such as LangChain, LangGraph, LlamaIndex, or similar. Experience integrating enterprise applications through APIs and authentication mechanisms (OAuth2, OIDC, JWT). Hands-on experience with AWS Cloud (preferred) or Microsoft Azure, especially AI-related services. Experience with Docker and basic CI/CD concepts. Experience with relational databases (PostgreSQL, SQL Server, MySQL) and familiarity with vector databases is a plus. Experience with frontend technologies (React, Next.js, Angular, or similar) is a plus. Experience with agent frameworks or open-source agent harnesses — LangChain/LangGraph, OpenClaw, Hermes-style agents, AutoGen, CrewAI — or a personal AI agent is a plus. Experience in Banking, Financial Services, or other regulated industries is an advantage. Strong analytical, problem-solving, communication, and teamwork skills. Logical thinking and self-learning habit; passion for continuous learning and adapting to emerging AI technologies Nanthipak ( May ) Mobile Phone: 082-9155978 Email nanthipakh@lhbank.co.th
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Most developer ads you'll see are written in English: 18,397 of the 24,795. That doesn't tell you whether the job itself requires you to speak English or work in English daily, so read each posting carefully. Don't assume the language of the ad matches the language of the team.
The employers posting the most developer roles are Link Group (369 jobs), Upvanta (257), jobgether (226), and OfferZen (212). If you're applying to any of these, research their hiring patterns. They move fast and post often, which means they're either scaling hard or replacing people who didn't fit.
In your interview, expect this: 'Walk me through the last time you had to debug something that took you more than an hour. What was it, what did you try first, and what would you do differently?' Hiring managers ask this to see if you think systematically or just try random fixes. Have a real example ready with specifics.