Python backend / Agent Engineer (Python + Gen‑AI)

Role Overview:
Our partner (headquartered in US, New York, NY) is looking for an innovative agent focused engineer to expand product agent back‑end so new automations can be shipped every week.

Responsibilities:

• Design and implement multi-agent orchestration systems, managing agent interactions, control transfers, and task coordination across specialized agents (planner, email analyzer, search, etc.)
• Develop and maintain agent configuration management systems including dynamic Firestore-based configurations, tool assignments, model selection, and prompt engineering for optimal agent performance
• Build and integrate custom tools and workflows for calendar management, memory systems, UI interactions, and email processing pipelines using sequential agent workflows
• Implement and optimize memory and context management including session handling, persistent user memory (Mem0 experience is a plus), and ensuring agents maintain relevant historical context
• Manage real-time agent communication systems including WebSocket connections, multi-modality support (text/audio/image), and background task processing for seamless user experiences
• Write evals and unit tests to ensure consistency 

Qualifications:

• Expert Python development with strong async/await programming patterns, FastAPI integration, experience with Google ADK (Agent Development Kit) framework or equivalent like LangChain, Crew or similar
• Deep understanding of LLM integration and prompt engineering, specifically with Gemini models, including model selection, response optimization, and token management
• Experience with cloud-native architectures including Firestore for configuration management, Google Cloud services integration, and microservices communication patterns
• Proficiency in building and maintaining tool ecosystems including calendar APIs, memory systems, search integrations, and custom function development for agent capabilities
• Strong background in AI/ML workflows including sequential processing, agent orchestration, error handling, performance optimization, and end-to-end testing of AI systems