At Ryz Labs we are looking for a Senior / Lead AI/ML Engineer to design and ship production-grade conversational AI agents with advanced tool use and orchestration capabilities. This is a hands-on role where you’ll work closely with the internal team to build, scale, and harden real-world LLM systems in a production AWS environment.
You’ll be embedded with the team, contributing directly to architecture decisions and implementation.
Key Responsibilities- Design and implement LLM-powered conversational agents in production
- Build robust agent orchestration systems, including:
- State management
- Pause/resume flows
- Journey and mode routing
- Failure handling and recovery
- Develop and integrate tooling via MCP or gateway-style architectures, including:
- Schema design
- Authentication & authorization
- Idempotency handling
- Auditability
- Create and maintain custom evaluation frameworks for LLM performance and reliability
- Operate and deploy systems in a production AWS environment
- Collaborate closely with internal stakeholders in an embedded delivery model
- Proven experience shipping production LLM agents with tool use
- Strong expertise in Python
- Hands-on experience with:
- Agent orchestration patterns (state machines, routing, retries, etc.)
- Tool integration frameworks (MCP or similar gateway approaches)
- Experience working in production AWS environments, including:
- EKS
- Lambda / EventBridge
- IAM
- Bedrock / Agent runtimes
- Logging and monitoring systems
- Experience with at least one LLM observability/evaluation platform in production (e.g., Arize AX, Langfuse, Phoenix)
- Experience with AWS Bedrock and AgentCore (Runtime + Gateway)
- Familiarity with Strands, or ability to ramp quickly from LangGraph / LangChain
- Experience implementing governed memory systems
- Background in regulated environments (fintech, banking, etc.)
Skills Required
- Proven experience shipping production LLM agents with tool use
- Strong expertise in Python
- Hands-on experience with agent orchestration patterns
- Experience working in production AWS environments
- Experience with at least one LLM observability/evaluation platform in production
What We Do
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