Full Description

Company Description Adroit Innovative Solutions is a US-based IT consulting and software development company dedicated to enabling businesses to achieve innovation, operational efficiency, and growth. Offering services in IT Consulting, Software Development, Data Engineering, Digital Transformation, and more, Adroit tailors technology solutions to meet diverse industry needs. Guided by core values such as integrity, innovation, and inclusion, the company is committed to building client-centric partnerships and delivering measurable outcomes. With a global presence, Adroit serves over 100 industries, helping businesses excel in their digital transformation journeys.

Job Title: Sr Automated Test Engineer – API Services

Location: Denver, CO only local W2/C2C 10+years needed

Duration: Long-term

Interview Process

1st Round: 30 Mints Video call

2nd Round: In-person interview About the Role We are looking for a Senior Automated Test Engineer to lead the design and implementation of automated testing strategies for API services. This role requires deep expertise in Postman, API testing best practices, and integration with CI/CD pipelines. You will also implement API service tracing and observability to monitor distributed transactions and ensure system reliability. Additionally, you will leverage predictive analysis to identify potential failure points and take proactive steps to mitigate risks. As a senior engineer, you will mentor junior team members, drive quality initiatives, and ensure our API ecosystem meets the highest standards of reliability, performance, and security. Key Responsibilities Lead the development and maintenance of automated test frameworks for RESTful and SOAP APIs using Postman and Newman. Define and implement test strategies, including functional, integration, regression, and performance testing. Create and manage complex Postman Collections, environments, and dynamic variables for scalable automation. Integrate automated tests into CI/CD pipelines (e.g., Jenkins, Azure DevOps, GitHub Actions) and optimize execution. Implement API service tracing using tools like OpenTelemetry, Jaeger, or Zipkin to validate distributed workflows and troubleshoot issues. Establish observability practices by integrating logs, metrics, and traces into monitoring platforms (e.g., Prometheus, Grafana, ELK stack). Apply predictive analysis techniques to identify potential API performance bottlenecks, reliability risks, and failure patterns. Develop proactive mitigation strategies, such as early alerts, fallback mechanisms, and automated recovery scripts. Collaborate with architects and developers to ensure API design supports testability, observability, and resilience. Perform root cause analysis for defects and drive continuous improvement in testing processes. Mentor and guide junior QA engineers on automation, observability, and predictive analysis best practices. Stay current with emerging tools, frameworks, and methodologies for API testing and tracing. Required Qualifications Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience). Over 10 years of experience in the Software Development Industry. 5+ years of experience in API testing and automation, with at least 2 years in a senior or lead role. Expert-level proficiency in Postman, Newman, and scripting with JavaScript for Postman tests. Strong understanding of RESTful APIs, HTTP methods, status codes, JSON/XML, and API lifecycle. Hands-on experience with CI/CD tools, version control (Git), and test reporting. Familiarity with API documentation standards (Swagger/OpenAPI). Experience with API service tracing, observability tools (OpenTelemetry, Jaeger, Zipkin, Prometheus, Grafana), and predictive analysis techniques. Preferred Skills Experience with performance and load testing tools (e.g., JMeter, Gatling). Knowledge of OAuth 2.0, JWT, and API security best practices. Familiarity with cloud environments (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Understanding of microservices architecture and distributed systems. Exposure to machine learning or statistical models for predictive failure analysis