Senior/Lead AI/ML Engineer

RYZ Labs; Buenos Aires; Presencial; ARS 98.909.173 - 127.168.937; Jornada completa

Descripción de la vacante

RYZ Labs is seeking a Senior / Lead AI/ML Engineer to design and implement production-grade conversational AI agents. The role requires proven experience with production LLM agents, strong Python expertise, and hands-on experience in AWS environments. Candidates will work closely with internal teams, contributing to architecture decisions and tool integration. Key responsibilities include building orchestration systems and operating in a production AWS environment. This is a hands-on position offering a dynamic work environment.

Formación

• Proven experience shipping production LLM agents with tool use.
• Strong expertise in Python.
• Hands-on experience with agent orchestration patterns.

Responsabilidades

• Design and implement LLM-powered conversational agents in production.
• Build robust agent orchestration systems.
• Develop and integrate tooling via MCP or gateway-style architectures.

Conocimientos

Production LLM agents with tool use

Python

Agent orchestration patterns

Tool integration frameworks

Production AWS environments

LLM observability/evaluation platforms

Herramientas

AWS EKS

AWS Lambda

AWS EventBridge

AWS IAM

AWS Bedrock

Descripción del empleo

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.)