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RYZ Labs

Nearshore AI engineering for enterprises.

Client Service Engineer Lead - Solutions Management

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeRemote in ArgentinaNo salary listed

About the Job

Requirements

  • Strong hands-on experience developing software with AI coding agents in real-world projects, including independently planning, executing, reviewing, and validating agent-assisted development work.
  • Practical experience with multi-agent workflows, including breaking down engineering tasks, delegating work across agents, coordinating dependencies, and reviewing and integrating outputs.
  • Experience with spec-driven development, translating requirements into specifications, implementation plans, and acceptance criteria to guide AI agents and support reliable delivery.
  • Ability to manage parallel engineering workstreams, coordinating agents and development tasks while maintaining context, resolving conflicts, and ensuring consistent implementation quality.
  • Strong engineering judgment when working with AI-generated code, including reviewing changes, debugging issues, validating behavior through testing, and taking ownership of the final result.
  • Advanced knowledge of Model Context Protocol (MCP), including hands-on experience implementing MCP-based integrations or tools.
  • Full-stack development proficiency and ability to build and maintain web applications across front-end and back-end technologies.
  • Strong expertise in API design and integration, with demonstrated experience building or consuming RESTful APIs and webhooks.
  • Experience using AI tools and APIs to build AI-powered client solutions.
  • At least five years of hands-on experience in technical support, customer-success engineering, or SaaS operations.
  • At least five years of SQL experience, including writing queries, analyzing data, and troubleshooting data-related issues.
  • Candidates must be able to discuss concrete examples of multi-agent workflows, spec-driven development, and parallel delivery they have personally implemented; familiarity with AI tools or occasional use of coding assistants alone is insufficient.
  • A bachelor's degree in Computer Science, Engineering, or a related field is listed as a nice-to-have qualification.

Responsibilities

  • Serve as a technical subject-matter expert for enterprise platforms, providing implementation guidance and troubleshooting support during client launches and deployments.
  • Work alongside clients during training and go-live activities, executing implementation tasks and resolving adoption blockers in real time.
  • Develop and deliver technical training, best-practice documentation, and configuration guides tailored to client use cases.
  • Track and communicate adoption metrics, including instances launched, users onboarded, and time to value.
  • Implement custom configurations, scripts, and lightweight development solutions for client-specific requirements, including dashboards, API integrations, data transformations, AI-agent configurations, and web-based applications.
  • Write and maintain full-stack code for client customizations and internal automation tools.
  • Architect and build web-based solutions tailored to client needs.
  • Coordinate with development teams on client-specific integrations, API customizations, and feature requests.
  • Develop workarounds for platform limitations and advocate for product enhancements based on recurring client needs.
  • Diagnose, troubleshoot, and resolve complex technical issues across enterprise platforms and client environments.
  • Perform root-cause analysis through SQL queries, log reviews, and systematic troubleshooting.
  • Implement short-term workarounds and contribute to long-term fixes.
  • Manage incidents end to end, including reproducing issues, assessing impact and priority, coordinating cross-functional resolution, validating fixes, and communicating outcomes to stakeholders.
  • Escalate issues to Engineering and Product teams while maintaining ownership of client communication and resolution tracking.
  • Support production incidents and urgent deployments in accordance with secure deployment processes.
  • Create and maintain knowledge-base articles, troubleshooting guides, and best-practice documentation.
  • Ensure technical content remains current with product releases.
  • Identify patterns in support tickets and recommend product or process improvements supported by data and evidence.
  • Automate repetitive support tasks through scripting and workflow automation to improve efficiency and reduce resolution times.
  • Contribute to quality-assurance activities, including test automation, regression testing, and user acceptance testing coordination for platform updates.
  • Partner with Product Management, Engineering, and Implementation teams to drive issue resolution and product improvements.
  • Participate in customer-success reviews and post-implementation check-ins to identify adoption opportunities and technical risks.
  • Mentor junior support team members and contribute to knowledge-sharing initiatives.

Desired Qualifications

  • Proficiency in Python or another modern programming language for backend development and scripting.
  • Experience with front-end frameworks such as React or Vue.
  • Experience with ServiceNow, ticketing systems, or support-management platforms.
  • Exposure to supply chain, procurement, or logistics.

About the Company

RYZ Labs

Nearshore AI engineering for enterprises.

Ryz Labs builds AI products for enterprises and platform companies by embedding senior Latin American AI engineers in a forward-deployed, nearshore model. They provide teams that design, build, and ship production AI apps, agents, and data products, primarily on Azure and other major clouds, working in US time zones. Clients include Univision, Fanatics, Serve Robotics, and Vayo Travel. The service lets clients hire senior LatAm AI engineers or full nearshore AI development teams in weeks rather than months. Their goal is to help enterprise customers accelerate AI product development with distributed, experienced teams that integrate with the client’s existing tech stack.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Los Angeles, CA
Founded
2021

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