Verification & Validation Engineer

Arrow•Northford, CT

22h•Onsite

About The Position

This role involves analyzing complex software requirements and designing data-driven validation strategies for web, mobile, and real-time embedded systems. The engineer will develop and execute automated test suites, build Python-based utilities for test automation, and analyze large volumes of test data to identify trends and defect patterns. The position also requires applying statistical and machine learning techniques for defect prediction and risk-based testing, integrating automation frameworks with CI/CD pipelines, and developing intelligent test case prioritization strategies. Additionally, the role involves creating dashboards for quality metrics, utilizing NLP-inspired approaches for requirement analysis, performing root cause analysis, and validating real-time embedded hardware-software systems, including working with low-level communication protocols like I2C. Ensuring data quality and awareness of bias in datasets is also crucial.

Requirements

Requires in-depth knowledge and experience
Solves complex problems; takes a new perspective using existing solutions
Works independently; receives minimal guidance
Acts as a resource for colleagues with less experience
Typically resolves problems using existing solutions
Provides informal guidance to junior staff
Works with minimal guidance
5–7 years of related experience with a 4 year degree; or 3 years and an advanced degree; or equivalent work experience.
Experience with Robot Framework and Python.
Experience with CI/CD pipelines.
Experience with embedded hardware–software systems.
Experience with low-level communication protocols, including I2C serial communication.

Nice To Haves

Represents the level at which career may stabilize for many years or even until retirement
Contributes to process improvements
Statistical and machine learning–oriented techniques using Python libraries.
NLP-inspired approaches.

Responsibilities

Analyze complex software requirements and design data-driven validation strategies for web, mobile, and real-time embedded systems.
Develop and execute robust automated test suites using Robot Framework and Python, leveraging a data-driven approach.
Design and implement Python-based utilities and scripts to support test automation, data processing, and result analysis.
Collect, preprocess, and analyze large volumes of test data, logs, and system outputs using Python to identify trends, anomalies, and defect patterns.
Apply statistical and machine learning–oriented techniques using Python libraries to support defect prediction, risk-based testing, and intelligent regression suite optimization.
Build and maintain scalable automation frameworks integrated with CI/CD pipelines.
Develop intelligent test case prioritization strategies based on historical execution data and system risk analysis.
Create dashboards and visual reports to present quality metrics, defect density, and predictive insights.
Utilize structured analysis of requirements and defect descriptions (NLP-inspired approaches) to improve traceability and test design accuracy.
Perform in-depth root cause analysis using data-driven methodologies.
Apply strong embedded hardware–software system understanding to validate real-time applications and ensure seamless interaction between firmware and software layers.
Work with low-level communication protocols, including I2C serial communication, to validate device-level interactions, timing, and data integrity.
Ensure data quality, consistency, and bias awareness in datasets used for testing and validation of intelligent and automated systems.
Design and development of real time software and Cloud/Web/mobile based software application.
Analyze domain specific technical, high level or low level requirement and modification as per end customer or system requirement.
Perform software testing including unit, functional and system level requirement including manual and automated.
Perform code review following coding guidelines and static code analysis & troubleshoots software problems of limited difficulty.
Document technical deliverable like software specifications, design document, code commenting, test cases and test report, Release note etc. throughout the project life cycle.
Develop software solutions from established programming languages or by learning new language required for specific project.
Develop new approaches to complex design problems.