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Senior/Lead AI/ML Engineer

Role overview

Qualifications

  • Proven experience shipping production LLM agents with tool use
  • Strong expertise in Python
  • Hands-on experience with agent orchestration patterns (state machines, routing, retries)
  • Experience working in production AWS environments including EKS, Lambda/EventBridge, IAM, Bedrock/Agent runtimes, logging and monitoring systems

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, and failure handling and recovery
  • Develop and integrate tooling via MCP or gateway-style architectures including schema design, authentication/authorization, idempotency handling, and auditability
  • Create and maintain custom evaluation frameworks for LLM performance and reliability; operate and deploy systems in production AWS environment

About the company

Ryz Labs logo

Ryz Labs

IT Services & IT Consulting

🤩 Where startups soar! We're not just building startups - we're crafting the future. From ideation to execution, we provide the blueprint for startup success. ✅ 💡 We specialize in nurturing startups from the ground up, and supercharging existing ones with our top-tier technical talent solutions. 🌐 Join us at Ryz Labs, where we turn promising ideas into thriving businesses. Let's shape the future of innovation together!

Company details

Company typeStartup
IndustryIT Services & IT Consulting
Company size11 - 50

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Job description

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

Required Qualifications

  • 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)

Preferred / Nice to Have

  • 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.)

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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