Senior AI Engineer
Skills
Agentic AI DevelopmentGoogle Cloud PlatformPythonMulti-Agent SystemsRag PipelinesVertex AiBigquery
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
