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

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
5+ years of experience in AI/ML
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

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonLangChainLlamaIndexGCP Vector SearchPineconeRAGSemantic SearchLLM fine-tuningEmbedding fine-tuningMLOps

Soft Skills

collaborationinnovationcustomer engagementproblem-solvingcommunication

Certifications

Bachelor’s degree in Computer ScienceMaster’s degree in Computer ScienceBachelor’s degree in EngineeringMaster’s degree in Engineering