AI Technical Architect, AI Preales

3 days ago

Bang Rak, Bangkok, Thailand Yip In Tsoi & Co., Ltd. Full time

Position Overview We are looking for a visionary AI Technical Architect to lead the design and implementation of our enterprise-grade AI infrastructure. You will bridge the gap between business requirements and cutting-edge AI/ML technologies, ensuring reliability, scalability, and security in every solution.

Responsibilities

  • Architecture Design: Lead the end-to-end design of AI systems, from data ingestion and model training to model serving and deployment across Cloud and On-premise environments.
  • Technology Selection: Evaluate and select the most appropriate frameworks and platforms (Build vs. Buy analysis), such as LLMs, Vector Databases, or MLOps tools.
  • Scalability & Performance: Optimize system performance, focusing on latency, throughput, and efficient resource management (GPU/TPU Optimization).
  • MLOps Implementation: Establish MLOps and CI/CD pipelines to streamline collaboration between Data Scientists and Developers, automating model retraining and deployment.
  • Governance & Security: Define and enforce standards for Data Privacy, AI Ethics/Bias, and Compliance.
  • Stakeholder Collaboration: Collaborate with Product Managers and Engineers to translate business goals into clear technical requirements.
  • Mentorship: Mentor the technical team to elevate skills and establish software development best practices.

Qualifications

  • Education: Bachelor's degree or higher in Computer Science, Computer Engineering, Data Science, or related fields (Master's or PhD preferred).

  • Experience:

  • 3-5+ years of direct experience designing and deploying AI/ML systems to production.

  • 7-10+ years in Software Engineering or System Architecture.
  • Strategic Thinking: Ability to see the big picture and solve complex technical challenges.
  • Communication: Excellent communication skills, capable of explaining deep technical concepts to non-technical stakeholders.
  • Language: Proficient in English (technical reading and communication required).

Required Technical and Professional Expertise

  • Core AI & Machine Learning:

  • Expert proficiency in Python; familiarity with C++ or Java.

  • Deep understanding of DL/ML Frameworks: PyTorch, TensorFlow, Scikit-learn, Keras.
  • Knowledge of Generative AI / LLMs: Transformers, RAG (Retrieval-Augmented Generation), Prompt Engineering, LangChain/LlamaIndex.

  • Cloud & Infrastructure:

  • Expertise in Cloud Platforms: AWS (SageMaker), Azure (AI Studio), or GCP (Vertex AI).

  • Containerization & Orchestration: Docker, Kubernetes (K8s) for AI Services.
  • Compute Resources: GPU utilization (CUDA), Distributed Training.

  • Data & Databases:

  • SQL, NoSQL, Data Lakes/Warehouses (Snowflake, BigQuery, Databricks).

  • Vector Databases: Pinecone, Milvus, Weaviate, or Elasticsearch.

  • MLOps & DevOps:

  • Experience with MLOps tools: MLflow, Kubeflow, Weights & Biases.

  • CI/CD: GitLab CI, Jenkins, GitHub Actions, and Terraform (IaC).
  • Architecture Patterns: Microservices, Serverless computing, and Event-driven architecture.

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