AI Deployment Specialist (SPX Express) - Operations - Bangkok

This role involves architecting and leading the deployment of AI-based applications and large language models (LLMs) across operational workflows. The specialist manages the full lifecycle of AI model integration, wrapping machine learning models into scalable APIs and integrating them into full-stack production systems. Responsibilities include designing automated CI/CD pipelines, managing infrastructure using Linux and containerization (Docker, Kubernetes), and implementing telemetry to monitor model performance and optimize systems to meet SLAs. The position requires collaborating with Data Scientists to transition models into production-ready code and with product teams to identify AI integration opportunities.

Scope, architect, and lead the deployment of AI-based applications and large language models (LLMs) across diverse operational workflows.

Manage the full lifecycle of AI model integration, wrapping machine learning models into robust, scalable APIs and integrating them into existing full-stack production systems.

Design and maintain automated CI/CD pipelines for machine learning models, ensuring seamless versioning, testing, and deployment without downtime.

Utilize Linux-based environments and containerization orchestration (Docker, Kubernetes) to provision, scale, and manage AI application infrastructure.

Implement comprehensive telemetry to monitor model performance, detect data/concept drift, and track system latency. Optimize deployed systems to meet strict service-level agreements (SLAs) and safety standards.

Partner actively with Data Scientists to transition models into production-ready code, and with product teams to identify new opportunities for AI integration.

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a closely related field.

3+ years of hands-on experience deploying, managing, and scaling AI/ML applications in live production environments.

Advanced proficiency in Python and modern web frameworks (e.g. FastAPI, Node.js). Full-stack development experience to build internal tooling and integration endpoints.

Mandatory proficiency in Linux systems administration, bash scripting, and resource management (CPU/GPU allocation).

Strong practical experience with major cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins).

Deep understanding of RESTful APIs, gRPC, and microservices architecture.

Experience using Terraform, CloudFormation, or Ansible to provision deployment infrastructure.

Direct experience deploying and optimizing generative AI models, working with frameworks like LangChain.