Advanced AI Software Architect

23 hours ago

Singapore beBeeGenerative Full time

AI Engineering Role

We are seeking a highly skilled and passionate AI Engineer with expertise in Generative AI to develop and implement cutting-edge AI solutions across cloud-native environments.

This role combines hands-on technical engineering with strategic leadership, enabling customers to translate AI innovation into scalable products from ideation to MVP and beyond.

Key Responsibilities:

  • Design, build, and deploy GenAI-driven applications using frameworks such as LangChain, OpenAI API, and Hugging Face Transformers.
  • Architect and implement scalable solutions within containerized, microservices-based cloud-native environments e.g., Kubernetes, OpenShift.
  • Integrate GenAI models and services seamlessly into existing platforms and services.
  • Collaborate with partner teams on advanced AI solution development.
  • Refactor and modernize legacy systems with 12-factor principles and cloud-native best practices.
  • Drive innovation in GenAI adoption through internal R&D, PoCs, and pilot programs.
  • Stay ahead of AI trends and apply the latest research into practical applications.
  • Provide expert consultation on GenAI architecture deployment strategies and business use case alignment.
  • Facilitate technical workshops presentations and strategic planning sessions with clients.
  • Serve as a trusted technical advisor on AI/ML integration helping clients unlock value from AI technologies.

Requirements:

  • Bachelor's degree in Computer Science Information Technology or a related field.
  • 5 years of software engineering experience with strong programming skills in Java and Python.
  • Deep expertise in Generative AI frameworks including LangChain OpenAI Hugging Face Transformers.
  • Strong foundation in Natural Language Processing NLP: tokenization embeddings transformers LLMs.
  • Experience with prompt engineering and optimizing AI model interactions.
  • Proven success designing and deploying cloud-native solutions using Kubernetes Docker and microservices.
  • Strong experience with Agile and DevOps practices working in Jira-based environments.
  • Hands-on experience with MLOps CI/CD for ML model versioning monitoring.
  • Proficiency in data engineering for AI: ETL feature pipelines data labeling quality control.
  • Knowledge of vector databases e.g. Pinecone FAISS Weaviate and retrieval-augmented generation RAG techniques.
  • Cloud certifications from AWS Azure or Google Cloud Platform GCP.

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