Senior AI Engineer

Skills
Agentic AI DevelopmentGoogle Cloud PlatformPythonMulti-Agent SystemsRag PipelinesVertex AiBigquery
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • Strong hands-on experience with Python for AI/ML application development and backend engineering
  • Proven expertise in Agentic AI autonomous AI agents and multi-agent orchestration frameworks
  • Experience building RAG pipelines prompt engineering embeddings vector databases and LLM integration
  • Strong experience with Google Cloud Platform GCP AI services including Vertex AI and BigQuery
  • Solid understanding of Foundation Models AI system architecture REST APIs and cloud-native application development

Day to day

  • Design and deploy intelligent Agentic AI solutions for enterprise use cases using single-agent and multi-agent architectures
  • Build scalable RAG pipelines that connect LLMs with enterprise knowledge bases and vector search
  • Develop production-ready AI systems on Google Cloud Platform using Vertex AI BigQuery and cloud-native infrastructure
  • Collaborate with cross-functional teams to integrate AI agents with enterprise data platforms APIs and business applications
  • Optimize AI models and workflows for performance scalability security and reliable deployment using software engineering best practices