Technical Specialist - AI Engineering
At a glance
Mid-level AI Engineering role at aCommerce. Bangkok.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build AI features for internal tools, services and automated workflows, including assistants and retrieval-based knowledge systems
- Create APIs and data pipelines that make AI systems dependable, scalable and safe to use
- Improve coding, testing and documentation workflows with AI-powered developer tools
- Assess AI models and platforms, then help shape adoption standards, governance and the wider roadmap
- Work with product, engineering and operations teams to turn needs into AI solutions and lead feature design discussions
What you bring
- At least five years working in software engineering
- You have built agent-based applications and can explain the tradeoffs between different approaches
- Strong ability in Python, Node.js/TypeScript or Go, plus working knowledge of SQL
- Practical experience with LLM APIs and context design, alongside familiarity with retrieval pipelines or vector databases
- You have built APIs, microservices or event-driven systems and used enterprise development, testing and delivery practices
Who this fits
This suits a hands-on software engineer who also wants to contribute to AI planning, evaluation and responsible use. The role is based in Bangkok, Thailand.
From the employer
Job Purpose
We are building AI‑powered systems that support multi‑marketplace operations, warehouse operations, financial workflows, and internal developer productivity across Southeast Asia. We’re looking for an AI Developer who can build real AI features and contribute to our broader AI strategy — helping shape how our teams adopt, scale, and govern AI across the company.
This role is perfect for someone who enjoys hands-on engineering but also wants to influence how AI is used at an organizational level. aCommerce is a learning organization, and we are looking for a contributor to that learning mindset who is specialized in software development that effectively incorporates LLMs.
Duties and Responsibilities
- Build and integrate AI features into internal tools, microservices, and automation workflows.
- Develop LLM‑powered assistants, RAG systems, and knowledge tools using models like Claude, GPT, and Gemini.
- Create APIs, pipelines, and services that make AI reliable, scalable, and safe.
- Improve developer productivity through AI‑augmented coding, testing, and documentation tools.
- Contribute to the company’s AI roadmap and help identify high‑impact AI opportunities.
- Evaluate new AI tools, models, and platforms — and recommend what we should adopt.
- Help define best practices for prompt engineering, model usage, and safe deployment.
- Support teams in adopting AI responsibly, including training, documentation, and internal guidelines.
- Work with architects to ensure AI systems follow governance, auditability, and data‑handling standards.
- Partner with product, engineering, and operations teams to translate business needs into AI solutions.
- Lead design discussions for new AI‑powered features and internal platforms.
- Help build a culture of experimentation and continuous improvement around AI.
Capabilities
- At least 5 years of software engineering experience.
- Proven experience working on agentic applications with the ability to articulate the tradeoffs between different approaches
- Strong skills in Python, Node.js/TypeScript, or Go. Good awareness of SQL
- Hands-on experience with LLM APIs and context engineering.
- Familiarity leveraging vector databases, RAG pipelines and memory systems
- Experience building APIs, microservices, or event‑driven systems.
- Experience with enterprise SDLC tooling including version control, CI/CD systems, testing methodologies as they pertain to generative and agentic applications.
- Interest in AI strategy, evaluation, and responsible AI practices.
- Curiosity, problem‑solving mindset, and willingness to explore new tools.
- Experience with delivering applications to Kubernetes runtime environments a plus
- Experience using workflow engines, automation, or internal developer platforms.