Associate AI Platform Engineer

Tech Sequence is a fast-growing technology startup founded by professionals from the United States and Vietnam, combining international expertise with local market insight to deliver innovative and practical technology solutions. The company specializes in technology consulting, digital transformation, software engineering, business process optimization, and smart infrastructure systems. Its capabilities include AI solutions, ERP and CRM implementation, custom web and mobile application development, ELV solutions, security systems, AI-powered video analytics, access control, network infrastructure, smart parking, and integrated facility technologies. Serving clients across manufacturing, logistics, commercial real estate, retail, and office environments, Tech Sequence helps organizations improve efficiency, strengthen security, optimize business processes, and build scalable technology platforms for sustainable growth. Backed by a leadership team with experience across the United States and Asia-Pacific, Tech Sequence combines startup agility with enterprise-level execution to help businesses transform challenges into measurable business outcomes.

You'll be part of the Digital Engineering / AI team at Tech Sequence, reporting to the Engineering Manager / Head of AI.

This is a Grade G2 role for candidates who execute defined workstreams independently. The AI Platform Engineer builds and maintains the internal platforms, infrastructure, and tooling that enable Tech Sequence's teams to develop, deploy, and operate AI and ML systems at scale. Working with ML, data, and DevOps teams, this role provides the paved paths — compute, data access, model serving, and developer tooling — that make AI delivery fast, reliable, and cost-efficient. The AI Platform Engineer owns the AI/ML platform across its lifecycle — infrastructure, orchestration, model serving, and self-service tooling — and is accountable for reliability, scalability, security, and cost. The ideal candidate combines strong software and infrastructure engineering with practical knowledge of the ML lifecycle, and can design and operate platforms used by many engineers.

Ramp up on our systems, codebase, and current projects in your first 30 days Own a defined area of work with minimal supervision by day 60 Deliver a complete piece of work end-to-end by day 90

Design, build, and operate scalable infrastructure for AI/ML workloads across cloud and, where needed, on-premise and GPU environments. Provide self-service tooling, templates, and APIs that streamline model development and deployment. Build and maintain model-serving, feature-store, and pipeline-orchestration platforms. Optimize compute, GPU utilization, and cost across training and inference. Ensure platform reliability, observability, security, and compliance across AI workloads. Implement access controls, secrets management, and data governance. Automate provisioning, CI/CD, and environment management for AI/ML teams. Support and enable engineers, and continuously improve the developer experience. Collaborate with ML, data, and DevOps teams and participate in architecture and code reviews. Contribute to shared platform components, standards, and best practices.

The AI Platform Engineer is evaluated against the skill matrix below — a primary technology stack complemented by secondary and adjacent skills.

Technologies

Python and/or Go, Kubernetes & Docker, cloud (AWS/Azure/GCP)

Terraform/IaC, CI/CD, model serving & orchestration (Kubeflow/Airflow/Argo)

GPU infrastructure, feature stores, observability, and cost optimization

Bachelor's degree in Computer Science, Software Engineering, or a related field; a Master's degree or relevant certification is a strong advantage. 2-4 years of software/infrastructure engineering experience, with hands-on work on platforms or infrastructure for ML/AI systems. Strong proficiency in Python and/or Go, and experience with cloud platforms (AWS, Azure, or GCP). Strong problem-solving, collaboration, communication, presentation, and English communication skills. Solid understanding of the ML lifecycle, model serving, and pipeline orchestration. Experience with containers and orchestration (Docker, Kubernetes), infrastructure-as-code (Terraform), and CI/CD. Familiarity with GPU infrastructure, observability, security, and cost optimization. Experience with ML platforms (e.g., Kubeflow, SageMaker, Vertex AI), feature stores, and workflow orchestrators (e.g., Airflow, Argo). Exposure to distributed training, high-scale inference, and data-platform engineering.

Reliability-minded, pragmatic, outcome-driven, and comfortable working through ambiguity. Self-driven, adaptable, and passionate about platforms, AI infrastructure, and continuous learning.

Opportunity to work directly with founders and leadership teams. Exposure to international projects and global clients. Dynamic, collaborative, and fast-growing startup environment. Professional development and career growth opportunities. Competitive salary and performance-based incentives. Flexible and innovation-driven working culture. If you are passionate about artificial intelligence, machine learning, and building intelligent, scalable systems, and contributing to high-impact products and client solutions, and are looking to grow your career in a dynamic international environment, Tech Sequence would love to hear from you.

Send your CV to hr@techsequence.com with the subject line: “Application for AI Platform Engineer - [Your Name]”Sincerely, Tech Sequence Recruitment Team