About the role
Responsibilities:
- Building task-specific AI agents for healthcare operations.
- Creating reusable agent architectures for multiple customers.
- Integrating LLMs with enterprise tools and APIs.
- Designing prompt pipelines and tool execution flows.
- Developing memory and context management for agents.
- Building fault-tolerant agent execution systems.
- Improving response quality, latency, and operational reliability.
- Multi-Agent and Workflow Orchestration: Build orchestration systems that coordinate multiple AI agents and external services.
This includes:
- Designing multi-step AI workflows.
- Agent-to-agent communication.
- Workflow routing and decision engines.
- Human-in-the-loop approvals.
- Retry and recovery mechanisms.
- Background job execution.
- Queue-based processing.
- Event-driven automation pipelines.
- You should enjoy solving real-world orchestration problems where reliability is as important as intelligence.
- Customer-Specific AI Automation.
- Every healthcare customer has different workflows.
- You will build configurable AI systems that can adapt to each customer's processes without requiring major code rewrites.
Examples include:
- Referral workflows.
- Appointment coordination.
- Document processing.
- Patient communication.
- Provider-specific automation rules.
- Portal and EHR integrations.
- Customer-specific business logic.
- Custom workflow builder.
- Backend Platform Engineering.
- Design scalable backend systems supporting AI workflows.
Responsibilities include:
- Building REST APIs.
- Backend microservices.
- Database design.
- Queue-based processing.
- Worker services.
- Authentication and authorisation.
- Third-party integrations.
- Logging and monitoring.
- Performance optimization.
- Cloud deployment.