Agentic AI Developer

Key Responsibilities:

• Design, build, and deploy intelligent AI agents using agentic frameworks.
  
• Develop RAG pipelines integrating vector databases and context-driven prompting strategies.
  
• Utilize the Gemini SDK to create LLM-powered applications and conversational interfaces.
  
• Collaborate cross-functionally with workflow orchestration and application development teams to deliver scalable AI solutions in production.
  
• Optimize agent performance and ensure robustness in real-world environments.
  

Requirements:

• 2–4 years of proven experience in GenAI and RAG application development.
  
• Strong hands-on expertise with GCP’s AI/ML stack.
  
• ADK (Agent Developer Kit)
  
• Gemini SDK
  
• Agent space
  
• Experience with vector databases such as Vertex AI Search, Pinecone, or FAISS.
  
• Strong proficiency in Python for building and integrating AI pipelines.
  
• Familiarity with frameworks like Lang Chain is a plus.
  
• Solid understanding of prompt engineering, agent orchestration, and tool usage.
  
• Exposure to cloud-native deployments such as Cloud Run, Vertex AI, or Firebase Functions.