About this role

Architect & Build: Design and implement end-to-end GenAI applications using Python, LangChain, and LlamaIndex on Google Cloud.
Engineer for Precision: Develop advanced RAG (Retrieval-Augmented Generation) pipelines and Semantic Search systems using GCP Vector Search or Pinecone.
Optimize Models: Lead efforts in LLM and Embedding fine-tuning to improve domain-specific performance.
Agentic Ops: Build and manage agentic workflows that automate complex multi-step reasoning tasks.
Collaborate & Innovate: Work directly with customers to understand requirements, suggest novel features, and implement state-of-the-art AI techniques.
Productionize: Apply MLOps best practices to ensure models are served efficiently, monitored, and continuously improved.

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
Proven track record of deploying GenAI products to a production environment.
Experience with Classic Machine Learning (neural nets, training, tuning) is a strong plus.
Knowledge of Data Engineering and SQL.

Senior AI Engineer

Key skills