about 5 hours ago
Responsibilities
- Design and implement LLM-based autonomous agents for planning, reasoning, and task decomposition.
- Engineer context-rich agents that integrate structured data and external APIs.
- Build orchestration frameworks for complex workflows in distributed microservices architectures.
- Implement agent-to-agent communication protocols for dynamic task delegation.
- Develop cloud-native infrastructure for agent deployment using Docker and Kubernetes.
- Ensure performance and monitoring in agent systems for large-scale fundraising workflows.
- Architect vector and graph database integrations for agent memory and semantic recall.
- Build custom frameworks for campaign storytelling and donor engagement.
- Scale LLM evaluation pipelines with safety and transparency measures.
Requirements
- 6+ years in software engineering with 3+ years in AI/ML systems.
- Deep expertise in LLM agent frameworks like LangGraph and Google ADK.
- Proven ability to architect agentic systems from scratch.
- Strong skills in Python and TypeScript with experience in microservices.
- Familiarity with vector databases and knowledge graphs.
- Knowledge of advanced reasoning, planning, and task decomposition in agents.
- Experience with RESTful APIs and A2A interoperability.
- Production experience with cloud-native infrastructure.
- Demonstrated experience with reinforcement learning and agent evaluation techniques.
- Strong understanding of agent safety and ethical design practices.
Benefits
- Make an impact in a mission-driven organization.
- Work in an innovative and collaborative environment.
- Enjoy competitive pay and comprehensive healthcare benefits.
- Receive financial assistance for hybrid work and family planning.
- Access generous parental leave and flexible time-off policies.
- Participate in learning and development programs.
- Contribute to diversity, equity, and inclusion initiatives.
- Engage in community volunteering programs.