Regional AI Engineer  

Position Responsibilities

AI Solution Development

  • Design, develop, and maintain AI-powered solutions to support business operations across regional markets.
  • Build AI applications using LLMs, AI APIs, AI agents, RAG, and other AI technologies.
  • Integrate AI capabilities into existing business systems, platforms, and workflows.
  • Develop solutions such as:
    • AI assistants and chatbots
    • AI agents for task automation
    • Document understanding and information extraction
    • AI-powered classification and routing
    • Knowledge-based Q&A / RAG applications
    • AI summarization and content generation
    • AI decision-support tools
  • Evaluate different AI models and services based on accuracy, cost, latency, security, and business requirements.
LLM & AI Integration
  • Integrate commercial and open-source AI models through APIs and SDKs.
  • Work with platforms such as OpenAI, Claude or equivalent AI services.
  • Build and maintain prompt templates, structured outputs, tool calling, function calling, and AI workflows.
  • Connect AI solutions with internal systems through REST APIs, webhooks, databases, and automation platforms.
  • Explore and implement AI Agent / MCP-based solutions where appropriate.
AI Automation
  • Combine AI capabilities with automation platforms such as n8n, Lark, and other internal automation tools.
  • Identify business processes where AI can reduce manual work, improve response time, or increase operational efficiency.
  • Build AI-assisted workflows that can understand information, make structured decisions, and trigger downstream actions.
  • Work closely with Automation Engineers to integrate AI components into end-to-end automation solutions.
AI Operations & Maintenance
  • Monitor AI applications and identify issues related to:
    • Model responses
    • Prompt failures
    • API errors
    • Latency
    • Token usage and cost
    • Data quality
    • Incorrect or unexpected outputs
  • Perform basic debugging and root-cause analysis.
  • Continuously improve AI solutions based on user feedback and production performance.
  • Establish appropriate AI evaluation, testing, monitoring, and quality-control mechanisms.
  • Maintain documentation covering architecture, prompts, models, APIs, data sources, and operational procedures.
AI Governance & Security
  • Ensure AI solutions follow company requirements for data privacy, access control, security, and responsible AI usage.
  • Understand the risks associated with confidential business data being sent to external AI services.
  • Implement appropriate controls for sensitive data, permissions, and AI-generated outputs.
  • Ensure AI applications have appropriate human review or approval mechanisms where required.
Regional Collaboration
  • Work with regional business, operations, product, technology, and data teams to understand AI opportunities and requirements.
  • Translate business requirements into practical AI solutions.
  • Support deployment and adoption of AI solutions across different countries and markets.
  • Understand regional differences in languages, processes, systems, and business requirements.
  • Communicate technical limitations, risks, and trade-offs clearly to stakeholders.
  • Escalate architecture, data, security, or AI-quality issues early.

Qualifications & Education

  • Bachelor’s degree in Computer Science, Information Technology, Software Engineering, Data Science, Artificial Intelligence, or a related field.
  • 1–3 years of experience in software development, AI engineering, automation engineering, or a related technical role.
  • Hands-on experience building applications using LLMs or AI APIs.
  • Strong analytical and problem-solving skills.
  • Ability to independently research, prototype, test, and deploy new AI technologies.
  • Good communication and interpersonal skills.
  • Ability to work independently while managing multiple AI projects.
  • Strong attention to detail and focus on reliability and quality.
  • Experience working with business stakeholders and translating business requirements into technical solutions is preferred.
Required Skillsets - AI & LLM
  • Basic to intermediate experience with LLMs and Generative AI.
  • Experience with at least one major AI platform/API such as OpenAI, Claude, Gemini, or equivalent.
  • Understanding of:
    • Prompt engineering
    • Structured outputs
    • Function/tool calling
    • Context windows
    • Token usage
    • Embeddings
    • RAG concepts
    • AI Agents
Required Skillsets - Programming
  • Basic to intermediate programming experience in Python or JavaScript/TypeScript.
  • Ability to read, modify, debug, and maintain existing code.
  • Understanding of software development fundamentals such as:
    • Functions
    • APIs
    • Error handling
    • Authentication
    • Data structures
    • Logging
Required Skillsets - API & Data
  • Good understanding of REST APIs & JSON.
  • Familiar with webhooks and asynchronous API interactions.
  • Basic to intermediate knowledge of SQL and databases.
  • Understanding of data transformation and validation.
Required Skillsets - AI Application Development
  • Experience building AI-powered applications, chatbots, assistants, or automation is preferred.
  • Familiarity with RAG / vector databases is a plus.
  • Familiarity with MCP (Model Context Protocol) or AI Agent frameworks is a plus.
  • Experience integrating AI with n8n, Lark, or other automation platforms is a plus.
Required Skillsets - Engineering & DevOps
  • Familiar with Git/GitHub and basic software development workflows.
  • Basic understanding of deployment, environment variables, authentication, and application configuration.
  • Familiarity with cloud services such as AWS, Azure, or GCP is a plus.
  • Experience with Docker/containerized applications is a plus.
a Necessity, not a Luxury