Remote QA Automation Engineer — Enterprise AI Platform

Data Squared; Philippines; Remote; PHP 5,629,000 - 8,130,000; Full time

Job summary

data² is a Decision Intelligence company delivering explainable AI that automates critical workflows and turns complexity into clarity. Our reView platform operates across AWS, containers, Kubernetes, and on-premises environments, with security and compliance as core pillars.

This remote QA Automation Engineer role focuses on shift-left testing, automated validation, and evidence-driven release readiness to support both Global Product and Federal delivery pipelines.

Qualifications

• Authorized to work in the United States and eligible to work within U.S.-controlled development, testing, and federal software-delivery environments, including access to export-controlled technical data.
• Strong experience testing backend systems, APIs, microservices, distributed systems, or complex enterprise platforms.
• Strong experience designing, implementing, and maintaining automated test frameworks.
• Strong Python skills and experience with pytest or similar frameworks.
• Experience designing automated integration and regression tests across multiple services.
• Experience integrating automated testing and quality gates into CI/CD pipelines.
• Experience testing applications and distributed services operating in AWS cloud environments.
• Experience with Docker and containerized development or test environments.
• Understanding of API contracts, authentication, authorization, error handling, asynchronous processing, and distributed-service behavior.
• Experience with performance, scalability, reliability, and failure-condition testing.
• Strong debugging and root-cause-analysis skills across multiple technical layers.
• Understanding of modern DevOps, shift-left quality, continuous testing, and continuous-delivery practices.
• Ability to translate product and technical requirements into objective automated validation.
• Strong written and spoken English for collaboration across a distributed engineering organization.

Responsibilities

• Embed quality and testability early in the development lifecycle.
• Partner with Product, Architecture, and Engineering to refine requirements, user stories, and acceptance criteria.
• Translate platform requirements into measurable, automatable test conditions.
• Define functional, integration, security, reliability, performance, and applicable accessibility acceptance criteria.
• Identify testability, observability, API contract, and error-condition requirements early in development.
• Apply BDD and structured test-design practices to critical platform capabilities and workflows.
• Design and maintain automated tests for FastAPI services, APIs, microservices, integrations, and critical workflows.
• Validate API contracts, authentication, authorization, error handling, asynchronous behavior, retries, timeouts, and recovery.
• Validate the ingestion and knowledge pipeline end to end (reDesign → reEnrich → reMap → reVeal → reFocus), including graph construction, entity resolution, relationship accuracy, and traversal correctness.
• Test positive, negative, boundary, exception, and failure conditions.
• Validate technical integrations with enterprise systems, identity services, and external services.
• Build regression coverage and reusable fixtures, mocks, and test data.
• Build evaluation harnesses for non-deterministic model output: retrieval precision and recall, answer accuracy, and grounding.
• Validate that reasoning stays bounded to the customer’s governed corpus and does not draw on model parametric knowledge.
• Validate Decision Record completeness, citation fidelity, source traceability, and reproducibility.
• Detect and regression-test hallucination, citation drift, and unsupported inference.
• Establish regression validation across model swaps, prompt changes, and retrieval-configuration changes, so a model upgrade cannot silently degrade explainability.
• Validate model-agnostic operation across supported LLMs and deployment modes, including locally hosted models in disconnected environments.
• Build and maintain the reusable automation capability supporting reView.
• Develop automated API, service, integration, functional, end-to-end, performance, reliability, security, and accessibility testing.
• Integrate automated testing throughout development and CI/CD pipelines.
• Establish automated quality gates and fast developer feedback.
• Support reliable execution across local, containerized, AWS, on-premises, and CI/CD environments - including validation paths for disconnected and air-gapped installations where pipeline egress is unavailable.
• Maintain high-value regression suites while improving execution speed, stability, diagnostics, and coverage.
• Generate automated quality evidence supporting Global Product and Federal releases.
• Security & Software Assurance: include automated software assurance, static analysis, secrets scanning, dependency vulnerability analysis, SBOM generation, and malicious-code scanning.
• Tools: CI/CD security and code-assurance tooling, SBOM tooling, Docker, Kubernetes, AWS.
• Performance, scalability, reliability & accessibility: establish baselines, run load tests, ensure accessibility and Section 508 compliance.

Skills

Python

pytest

BDD

Jira

Cucumber

SpecFlow

boundary analysis

equivalence partitioning

Tools

Docker

Kubernetes

FastAPI

Graph databases

CI/CD tooling

AWS

Grafana

Loki

Job description

data² is a Decision Intelligence company delivering explainable AI that automates critical workflows and turns complexity into clarity. Our reView platform operates across AWS, containers, Kubernetes, and on-premises environments, with security and compliance as core pillars.

This remote QA Automation Engineer role focuses on shift-left testing, automated validation, and evidence-driven release readiness to support both Global Product and Federal delivery pipelines.