Automation Architect - AI, Cloud & Quality Engineering

BridgeNexus Technologies Inc
Austin, TX, United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$129,939.0 - $140,400.0
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) JavaScript (Programming Language) Application Programming Interfaces (APIs) Agile Methodology Artificial Intelligence Amazon Web Services Automation of Tests Microsoft Azure C Sharp (Programming Language) Cloud Computing Code Coverage Continuous Integration
+36 more
Data Validation DevOps Distributed Systems Amazon DynamoDB Github Junit Python (Programming Language) PostgreSQL MongoDB Scrum Methodology Redis Cloud Services Selenium Software Engineering Data Streaming Systems Architecture Testng TypeScript Scripting Google Cloud GitHub Copilot Large Language Models Generative AI Event Driven Architecture Pytest Integration Tests Kubernetes Playwright Functional Programming Teamcity Amazon Simple Queue Service (SQS) Domain Driven Design GPT Docker Jenkins Microservices

Job description

Collaborate closely with developers to understand system architecture, data flows, and event-driven behaviors for effective automation design.

Build and enhance end-to-end automation frameworks supporting API, integration, and data validation layers.

Develop integration test suites to ensure reliability and stability across development and pre-production environments.

Automate regression, functional, and event-driven validations using Playwright, PyTest, TestNG, and related tools.

Contribute to modernization initiatives transitioning from legacy to distributed systems, ensuring comprehensive automation coverage and system resilience.

  1. AI & Intelligent Test Enablement

Leverage tools such as GitHub Copilot, ChatGPT, and LLM-based agents to assist in automation scripting, test generation, and analysis.

Integrate GenAI tools for test documentation, failure triage, and predictive quality analytics.

Experiment with autonomous testing agents capable of self-triggering and monitoring test pipelines.

Drive the adoption of AI-enhanced automation strategies to improve efficiency, quality insights, and test coverage.

  1. Cloud & DevOps Integration

Integrate automation frameworks within CI/CD pipelines (GitHub Actions, Jenkins, TeamCity) to enable continuous validation.

Deploy and manage test environments on AWS (EKS, SQS, Glue, Lambda, DynamoDB, PostgreSQL).

Implement observability and test telemetry to monitor pipeline health, performance, and coverage trends.

Collaborate with DevOps and platform engineering teams to ensure environment consistency, scalability, and release readiness.

  1. Agile Collaboration & Leadership

Actively participate in Agile/Scrum ceremonies-including sprint planning, daily standups, and retrospectives-to align testing and development objectives.

Mentor engineers in automation best practices and modern framework adoption.

Foster cross-functional alignment by collaborating with developers, architects, and product owners to ensure quality is engineered from the start.

Champion a quality-first culture by embedding continuous testing and automation throughout the delivery lifecycle.

Tech Stack & Tools

Languages: Java/C#/ Python, JavaScript/TypeScript

Frameworks: Playwright, Selenium, PyTest, TestNG, JUnit

Cloud & DevOps: AWS (EKS, Glue, SQS, Lambda, DynamoDB), Jenkins, GitHub Actions, Docker, Kubernetes

Databases: PostgreSQL, Redis, DynamoDB, MongoDB

AI Tools: GitHub Copilot, ChatGPT, OpenAI Assistants

Methodologies: Agile, Scrum, Domain-Driven Design, Event-Driven Architecture

Requirements

Do you have experience in TestNG?, Experience in test automation and quality engineering within complex enterprise environments.

Strong understanding of software development workflows with proven collaboration alongside development and architecture teams.

Expertise in Playwright and API automation frameworks, with proficiency in Java, Python, or C#.

Experience testing event-driven systems and microservice-based architectures.

Hands-on experience with AWS cloud services and CI/CD automation practices.

Exposure to GenAI tools (Copilot, ChatGPT, LLM-based assistants) for enhanced automation productivity.

Proven experience working in Agile/Scrum environments as an active and contributing team member.

Preferred Qualifications

Knowledge of AI-based automation, autonomous test agents, or intelligent QA platforms.

Certifications in AWS DevOps, Google Cloud, or Azure Fundamentals.

Experience with financial systems or data-intensive platforms.

Strong leadership and communication skills, with a passion for mentoring and cross-functional collaboration.

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