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Application Technical Lead - GenAI ($70-90k + bonus)

Job description

It is a leading financial institution with solid business in Hong Kong, with expanding use of AI into their operations.

Responsibilities

  • Lead design and development of enterprise GenAI platforms, covering model hosting, RAG pipelines, vector search, prompt lifecycle, guardrails, and monitoring.
  • Architect secure, scalable GenAI solutions integrating LLMs with internal systems and data sources.
  • Build reusable GenAI components, APIs, and frameworks to support high‑value use cases across operations, risk, compliance, investment, and internal productivity.
  • Evaluate and integrate commercial and open‑source LLMs, orchestration frameworks, and developer toolkits.
  • Oversee engineering teams delivering GenAI applications, prototypes, and production services with strong reliability and performance.
  • Establish best practices for prompt design, model evaluation, optimization, and safe AI deployment.
  • Collaborate with architecture, cloud, cybersecurity, compliance, and governance teams to ensure regulatory‑aligned AI usage.
  • Lead MLOps/LLMOps processes for model deployment, versioning, monitoring, and automation.
  • Partner with senior business stakeholders to define use‑case roadmaps and technical implementation plans.
  • Contribute to enterprise AI standards, platform governance, and engineering patterns.

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, or related technical fields.
  • 8-12+ years in software engineering or architecture, with recent years in AI/ML or GenAI.
  • Hands‑on experience with LLM integration, RAG pipelines, embeddings, and vector databases (e.g., FAISS, Pinecone, Milvus, Weaviate).
  • Strong proficiency in Python, APIs, microservices, cloud-native development, and distributed systems.
  • Experience building or operating GenAI platforms, including prompt libraries, guardrails, evaluation frameworks, and observability.
  • Working knowledge of MLOps/LLMOps, CI/CD, containerization, and model lifecycle management.
  • Understanding of financial‑sector requirements for data protection, cybersecurity, and responsible AI.
  • Proven track record delivering complex platforms in enterprise environments.
  • Excellent communication and stakeholder‑management skills in both Chinese and English.