Genai Software Architect

Intel · Semiconductors · Shanghai, China +1

GenAI Software Architect role focused on building and optimizing machine learning products and solutions, particularly LLM-based systems and AI agents. Requires deep expertise in GenAI algorithms, solution architecture, performance tuning, and experience with frameworks like LangChain, RAG pipelines, and vector databases. The role involves developing custom AI tools and optimizing GenAI workloads for edge devices.

What you'd actually do

  1. Builds machinelearning based products/solutions which provide descriptive, diagnostic, predictive, or prescriptive models based on data.
  2. Uses or develops machinelearning algorithms such as supervised and unsupervised learning, deep learning, reinforcement learning, Bayesian analysis, and/or others to solve applied problems in various disciplines such as data analytics, computer vision, and robotics.
  3. Interacts with users to define requirements for breakthrough product/solutions.
  4. In either research environments or specific product environments, utilizes current programming methodologies to translate machine learning models and dataprocessing methods into software.
  5. Completes programming, testing, debugging, documentation and/or deployment of libraries.

Skills

Required

  • AI/ML algorithm development
  • NLP
  • LLM-based systems
  • AI agent development
  • GenAI algorithms
  • Solution architecture
  • Performance tuning
  • Building custom AI tools, agents, or apps
  • Python
  • LangChain
  • LlamaIndex
  • AutoGen
  • HuggingFace
  • RAG pipelines
  • Vector databases
  • Embedding techniques
  • Optimizing GenAI workloads for edge devices
  • xPU accelerators
  • Local LLMs
  • Fine-tuning open-source models

Nice to have

  • customer/partner support for GenAI workflow design and deployment
  • client AI tools
  • cross-platform agents
  • plugin ecosystems
  • UX/UI
  • prompt engineering

What the JD emphasized

  • 10+ years hands-on experience on AI/ML algorithm development
  • 5+ years of hands-on experience in NLP, LLM-based systems, or AI agent development
  • Deep expertise in GenAI algorithms, solution architecture, and performance tuning
  • Proven experience building custom AI tools, agents, or apps for real-world use cases
  • Experience optimizing GenAI workloads for edge devices using xPU accelerators

Other signals

  • Builds machine learning based products/solutions
  • Uses or develops machine learning algorithms
  • Proven experience building custom AI tools, agents, or apps for real-world use cases
  • Experience optimizing GenAI workloads for edge devices