About the role
TL;DR
Lead AI Engineer responsible for full lifecycle of GenAI features, focusing on document intelligence and RAG pipelines.
- •As a Lead AI Engineer, you will be at the forefront of our Generative AI initiatives, treating AI as a software engineering discipline.
- •You will be responsible for the full lifecycle of AI features, from prototype to production, focusing on document intelligence and RAG pipelines.
- •Key Responsibilities Architect & Build end-to-end GenAI applications using Python, LangChain, and LlamaIndex on Google Cloud.
- •Develop advanced RAG pipelines and Semantic Search systems using Google Cloud Vector Search or Pinecone.
- •Lead efforts in LLM and Embedding fine-tuning to improve domain-specific performance.
- •Productionize models using MLOps best practices for efficient serving, monitoring, and continuous improvement.
- •Requirements Mastery of Python and shell scripting.
- •Extensive experience with Google Gemini, GPT-4, or LLaMA; deep knowledge of Prompt Engineering and Fine-tuning.
- •Expertise in Vector Databases and implementing Semantic Search.
- •Hands-on experience with Google Cloud (Vertex AI) and building scalable software architectures.
- •A strong software engineering foundation with understanding of the full SDLC.
Required skills
PythonBashOpenAI APILangChainVertex AIGoogle CloudSQL
Nice-to-have skills
scikit-learn
Domain expertise
aiconsulting
Tech stack
PythonBashOpenAI APILangChainVertex AIGoogle CloudSQL
