aimlroles

AI Engineer and Data Specialist

OOCA Open · verified Oct 22, 2026
On-site Bangkok Full-time Mid-level AI Engineering

At a glance

Mid-level AI Engineering role at OOCA. Bangkok · full-time.

Pay not stated AI Engineering salary

RoleAI Engineering
SeniorityMid-level
LocationBangkok
WorkplaceOn-site
EmploymentFull-time
PostedSep 24, 2026 · 4w ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build LLM pipelines and RAG systems, including retrieval, document indexing, context assembly and tool use
  • Create agent workflows, then test model behavior with structured suites, generated questions and benchmark data
  • Work with product and domain experts to turn unclear needs into defined LLM tasks and address issues such as hallucinations
  • Develop backend services and deploy LLM workloads on cloud or on-prem infrastructure, using evaluation and versioning to keep releases testable
  • Build GCP infrastructure and backend microservices, then connect them to user-facing Flutter interfaces

What you bring

  • A computer science, data, engineering or related degree, or equivalent practical experience
  • One to three years in data, AI, analytics or software work, or a strong project portfolio demonstrating comparable ability
  • Practical Python and SQL skills for data work, API use, scripting, and querying relational databases
  • Project experience with LLM or AI APIs, plus familiarity with at least one dashboarding tool
  • Clear Thai communication and working English for tools, documentation and some conversations

Who this fits

This mid-level, full-time role is based onsite in Bangkok. It suits someone with practical AI project experience who can work independently and deliver to agreed timelines. Strong fresh graduates may also fit if they have a solid portfolio.

From the employer

Key Responsibilities

  • Design, build, and optimize LLM pipelines including retrieval, context assembly, grounding, prompting, and tool-calling.
  • Develop RAG systems using vector databases, metadata design, chunking strategies, and hybrid retrieval approaches.
  • Build agentic workflows and function-calling systems capable of reasoning, planning, and executing tasks.
  • Evaluate model performance using structured test suites, synthetic QA generation, and benchmark datasets.
  • Work closely with product and domain experts to translate ambiguous requirements into clear, structured LLM tasks.
  • Diagnose and mitigate failure modes such as hallucinations, retrieval misses, and context collisions.
  • Apply lightweight fine-tuning or LoRA when needed for task-specific improvements.
  • Develop and maintain backend components for LLM pipelines (FastAPI, event systems, queues).
  • Prepare unstructured documents (PDFs, HTML, logs, knowledge bases) for ingestion and indexing in vector/RAG systems.
  • Support deployment across cloud or on-prem infrastructure (vLLM, TGI, Ollama, GPUs, token-budgeting).
  • Ensure all AI features are grounded, safe, testable, reproducible, versioned, and backed by real evaluation—not guesswork.
  • Design, deploy, and maintain cloud infrastructure on Google Cloud Platform (GCP) using GKE, Cloud Run, and CI/CD pipelines to support scalable LLM deployments and services.
  • Build end-to-end applications by developing high-performance backend microservices with Node.js/Go and integrating user-facing interfaces using Flutter.

Requirements

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, Statistics, or related field; or equivalent practical experience.
  • 1–3 years of experience in a data / AI / analytics / software role, or strong project portfolio demonstrating equivalent capability (strong fresh graduates will be considered if portfolio is solid).
  • Practical proficiency in Python for:
    • Data handling (e.g. pandas, basic NumPy)
    • Calling APIs and working with JSON
    • Writing small scripts/services
  • Practical proficiency in SQL (e.g. MySQL, PostgreSQL) for querying, joining, and aggregating data.
  • Experience with at least one BI / dashboarding tool (Looker Studio, Metabase, Power BI, Tableau, or similar).
  • Hands-on experience using LLM / AI APIs in projects (personal, academic, or production), not only theoretical knowledge.
  • Ability to structure problems, work independently on tasks, and deliver within agreed timelines.
  • Ability to communicate clearly in Thai, with working proficiency in English for tools, documentation, and some communication.

Benefits

  • Health Insurance
  • Hybrid
  • Annual Leave 12 days
  • Mental Health counseling sessions with psychiatrists and psychologists through ooca platform
  • Social Security Insurance
  • Provident Fund (condition applied)
  • Annual Health check-up (condition applied)
  • Special discount home loan interest with Government Housing Bank
  • BYOD policy: Personal laptops less than 3 years old are eligible for 1000 THB/month subsidy (registration required)