QA Engineer

Posted 5 Days Ago
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11 Locations
Remote
Senior level
Information Technology • Professional Services • Software
The Role
Lead QA efforts for LLM and agentic AI systems: build and maintain AI evaluation frameworks, design statistical tests for non-deterministic outputs, develop automated end-to-end and integration tests (backend, ingestion, inference, frontend), support CI/CD quality gates, participate in incident triage and SOC 2 Type II audit artifacts, and collaborate with engineering and client teams on production validation.
Summary Generated by Built In

We are looking for a QA Engineer based in Latin America to work on a long-term project for one of our clients, a Software Development company based in Atlanta, Georgia.

Our client is building a secure, bank-grade AI infrastructure and developing cutting-edge applications designed to power the next generation of modern banking and financial services.

Responsibilities

  • Contribute to the development and maintenance of the AI evaluation framework for LLM and agentic AI outputs across Foundry, Agent Builder, and client-deployed environments, in collaboration with the QA Lead.
  • Define and implement test assertions for new AI workflows, establish behavioral contracts under the guidance of the QA Lead, and help maintain regression baselines for model behavior across releases.
  • Apply advanced QA approaches for non-deterministic AI outputs, using statistical reasoning (e.g., distributions and confidence intervals) instead of purely deterministic assertions, particularly when evaluating complex tasks such as summarization of long-form documents (e.g., loan agreements).
  • Develop and maintain significant portions of the automated test suite, including end-to-end, integration, and regression tests covering backend APIs, document ingestion pipelines, AI inference workflows, and frontend surfaces.
  • Contribute to performance and load testing for latency-sensitive inference paths.
  • Ensure CI/CD quality gates remain stable and effective, and actively support the team in resolving pipeline failures.
  • Participate in production incident triage, create reliable reproduction cases for identified issues, and implement regression tests to prevent recurrence.
  • Produce test artifacts, audit logs, and process documentation supporting SOC 2 Type II compliance under the direction of the QA Lead.
  • Partner with Forward Deployed Engineering to support client-side validation, investigate production issues, and assist with reproduction of real-world customer scenarios.

Requirements

  • Advanced Level of English.
  • 5+ years of hands-on Software Quality Assurance/Quality Engineering experience, with strong software engineering and test automation skills, including experience testing complex distributed systems and at least 1 year of hands-on testing and validation of AI/ML systems.
  • Experience designing and executing test cases for Large Language Model (LLM) outputs, working within evaluation pipelines, and distinguishing between flaky tests and expected non-deterministic behavior in AI systems.
  • Proficient in Python and TypeScript, with hands-on experience developing and maintaining automated test suites using pytest and Playwright.
  • Hands-on experience with AI evaluation frameworks and tools such as RAGAS, DeepEval, LangSmith, or comparable LLM evaluation and testing solutions.
  • Ability to independently troubleshoot and trace failures across the full technology stack—from application layer to infrastructure—with practical knowledge of Microsoft Azure, asynchronous/distributed systems, and REST APIs.
  • Experience developing and maintaining automated tests within CI/CD pipelines, with a strong understanding of release quality gates and the ability to distinguish between controls that effectively mitigate risk and those that unnecessarily impede delivery.
  • Strong collaboration and communication skills, with the ability to work effectively with QA Leads, fellow QA engineers, and software engineers to ensure product quality and successful delivery.

Bonus Points

  • Bachelor’s Degree in Computer Science, Systems Engineering or related fields.
  • Experience in fintech, banking, or other highly regulated industries.
  • Familiarity with document processing pipelines, multi-agent AI architectures, Retrieval-Augmented Generation (RAG) validation, and observability platforms such as Arize, Langfuse, or similar AI monitoring and evaluation tools.

What we offer

  • Long term positions
  • Compensation in USD
  • Paid time off
  • Cool clients and products
  • Work with great engineers

4tech


Skills Required

  • Advanced level of English
  • 5+ years of Software Quality Assurance Engineering experience, including at least 1 year testing and validation of AI/ML systems
  • Experience designing and executing test cases for LLM outputs and evaluation pipelines; distinguishing flaky tests from expected non-deterministic behavior
  • Proficiency in Python and TypeScript
  • Hands-on experience developing and maintaining automated test suites using pytest and Playwright
  • Hands-on experience with AI evaluation frameworks/tools (e.g., RAGAS, DeepEval, LangSmith, or comparable)
  • Ability to troubleshoot and trace failures across full stack with practical knowledge of Microsoft Azure, asynchronous/distributed systems, and REST APIs
  • Experience developing and maintaining automated tests within CI/CD pipelines and understanding release quality gates
  • Strong collaboration and communication skills to work with QA Leads, QA engineers, and software engineers
  • Bachelor's Degree in Computer Science, Systems Engineering or related fields
  • Experience in fintech, banking, or other highly regulated industries
  • Familiarity with document processing pipelines, multi-agent AI architectures, RAG validation, and observability platforms (Arize, Langfuse, or similar)
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The Company
119 Employees
Year Founded: 2017

What We Do

Prediktive is a technology business partner and engineering services company that helps tech-enabled companies build and scale digital products. It provides software product development execution, engineering talent, and global remote support for startups, midsize businesses, and enterprises. Established in Silicon Valley, the company works across fields and time zones, connecting qualified professionals with client projects and helping organizations grow with confidence.

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