Senior/Lead AI/ML Engineer

Ryzlabs; Buenos Aires; Presencial; ARS 2.000.000 - 3.000.000; Jornada completa

Descripción de la vacante

Ryz Labs is seeking a Senior / Lead AI/ML Engineer to design and ship production-grade conversational AI agents in a hands-on role. You’ll work with an embedded delivery model to scale and harden real-world LLM systems in a production AWS environment.

You’ll influence architecture decisions and implementation, collaborating with internal teams to deliver robust, auditable agent solutions that leverage tool use and orchestration patterns.

Formación

• Production LLM agents with tool use
• Proficient in Python
• Agent orchestration patterns and tool integration frameworks
• Production AWS environments (EKS, Lambda, EventBridge, IAM, Bedrock)
• LLM observability/evaluation platforms (e.g., Arize AX, Langfuse, Phoenix)

Responsabilidades

• Design and implement LLM-powered conversational agents in production
• Build robust agent orchestration systems with state management, pause/resume, routing, and recovery
• Develop and integrate tooling via MCP or gateway-style architectures (schema design, auth, idempotency, auditability)
• Create and maintain custom evaluation frameworks for LLM performance and reliability
• Operate and deploy systems in a production AWS environment
• Collaborate with internal stakeholders in an embedded delivery model

Conocimientos

Python

LLM agents

Agent orchestration

Tool integration

AWS production

LLM observability

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.)