Pay Range:

POSITION SUMMARY:

Software quality is a critical component of R&D Systems’s transformation toward a digital laboratory and AI-driven data platform. This role designs and implements advanced test automation solutions across instrument software, data pipelines, analytics platforms, and AI-enabled applications.

The Sr. Test Automation Engineer will work across modern lab ecosystems including instrument software, ELN platforms, LIMS systems, cloud data platforms (e.g., Databricks), and AI/analytics applications to ensure data integrity, traceability, and system reliability.

This role partners with software, data engineering, IT, and scientific teams to validate end-to-end workflows spanning instrument  data pipelines  cloud analytics  AI/ML use cases, ensuring compliance with Quality System and regulatory requirements.

We're rethinking protein tools and helping thousands of researchers around the world resolve their protein analysis problems so they can reveal new insight into proteins and their role in disease.  Software is vital to our success in developing award winning bio-tech instruments for the life sciences industry.  Our product development team is making products that are drastically changing how scientists and researchers use tools to become more productive. Use your strong knowledge of test automation to expand the reliability of our instrument systems. You will collaborate with other software engineers and scientists in the development of analytical applications, working on design of graphical data presentations, algorithms, device communications, and complex data workflows.  We are offering an opportunity to work with state of the art software/hardware technologies amongst a very creative, motivated, and talented team.

ESSENTIAL FUNCTIONS:

• Design and implement AI-assisted test generation and validation (e.g., leveraging LLMs for test case creation, coverage analysis)

• Validate AI/ML outputs, including analytics dashboards, predictions, and query-based insights

• Develop data validation frameworks to ensure correctness of AI-ready datasets (FAIR principles, schema validation)

• Develop automated validation for data pipelines (ETL/ELT) including ingestion, transformation, and storage

• Validate structured data across systems such as Databricks, cloud data lakes, ELNs, and LIMS

• Implement automated checks for: Data completeness, Schema consistency (JSON/CSV outputs), transformation correctness

• Design test strategies for end-to-end lab workflows: Instrument software  export (CSV/JSON), Data ingestion into analytics platforms, Integration with ELN/LIMS systems

• Validate interoperability across systems (instrument, cloud, ELN, LIMS)

• Integrate test automation into cloud-based CI/CD pipelines

• Collaborate with the team to maintain and update test domain systems, including rack systems, instruments, and network infrastructure

• Implement test orchestration for distributed systems

• Disciplined and detail-oriented; deliver robust, readable code

• Key contributor to new software test solution architectures and design decisions

• Engage in the software lifecycle of test tools

• Ensure traceability between: Requirements, Test cases, Data outputs

• Ensure that all verification activities are conducted in accordance with Quality System requirements

• Determination and sound technical judgment in problem solving, analytical techniques, develops new / creative test designs, and can work independently with little supervision

• Input into appropriate test automation tools, applying the techniques in test automation; e.g., data-driven testing.

• Develops and writes automated test scripts and plans to ensure that software functions as expected.

• Prepares data sets to test logic, error handling and system workflows.

• Conducts testing of various features. Verifies fixes.

• Reviews and provides feedback to software requirements, specifications, user manuals, or other technical publications.

JOB SPECIFICATIONS:

Education and Experience:

Position requires a Bachelor’s degree in Computer Science or equivalent with a minimum of 6+ years test automation experience or relevant experience and training. 

Knowledge, Abilities:

• Familiarity with off the shelf test automation tools (e.g. TestComplete, Ranorex, Squish)

• Strong written skills necessary to document software and test procedures

• Ability to work within an agile test development environment

• Skills in problem solving; including the ability to identify and appropriately evaluate a course of action. 

• Experience executing to verification plans

• Ability to act independently on routine assignments or projects.

• Ability to plan, organize and multi-task to complete assignments in an efficient manner.

• Ability to communicate professionally, both oral and written.

• Ability to pay attention to details and perform at a high level accuracy.

• Ability to work independently and with a team.

Core Technical Skills

• Programming: Python (required), SQL, APIs, React, Flask, shell scripting

• Data Platforms: Databricks, Spark, SQL warehouses (preferred)

• Cloud Platforms: Azure / AWS / GCP (storage, compute, pipelines)

• Data Formats: JSON, CSV, Parquet, structured schemas

Test Automation & Quality Engineering

• UI/API Testing: Existing tools (TestComplete, etc.) + modern frameworks

• Data Testing:

  • Validation of pipelines

  • Schema testing

  • Data quality frameworks

• CI/CD:

  • GitHub / GitLab

  • Jenkins or modern cloud pipelines

AI / Advanced Testing

• Familiarity with:

  • AI-assisted testing tools

  • Prompt-based validation

  • Testing AI/ML outputs

• Understanding of:

  • Data quality impact on AI systems

  • Awareness of how poor-quality inputs can degrade AI outputs

Digital Lab Ecosystem

• Experience working with:

  • ELN platforms (e.g., Benchling, LabArchives)

  • LIMS systems

  • Scientific instrumentation software

• Understanding of:

  • Lab workflows

  • Scientific data lifecycle