Sr Software Quality Engineer (Exp w/ AI Techniques)

Aspen Technology, Inc.; Bedford (MA); On-site; USD 90,000 - 113,000; Full time

Benefits offered by this job

Medical/dental/vision insurance

Paid time off

Bonus or variable incentive pay

Retirement benefits

Charitable giveback day

Job summary

AspenTech is seeking a Senior Automation and AI-Driven Quality Engineer to design, implement, and scale intelligent quality, automation, and performance engineering solutions across enterprise-grade AI-enabled platforms. This hands-on role partners with product engineering, DevOps, and data/AI teams to embed Built-In Quality into the SDLC.

Responsibilities include designing AI-driven automation, implementing AI-assisted testing and test generation, and building scalable automation frameworks for

Qualifications

• BS/MS in Computer Science, Engineering, or related field.
• 5+ years of software engineering with a strong focus on automation, quality engineering, or performance engineering.
• Experience with AI/ML-assisted testing, LLM-based automation, or intelligent quality systems.
• Strong programming skills in Python, Java, C#, or JavaScript/TypeScript.
• Hands-on experience building test automation frameworks and integrating them into CI/CD pipelines.
• Experience with cloud platforms (Azure), microservices, and distributed systems.
• Solid understanding of Agile/SAFe delivery models and enterprise-scale software development.
• Excellent problem-solving, communication, and cross-team collaboration skills.
• Familiarity with performance testing tools (e.g., JMeter, Gatling, K6) and observability stacks.
• Experience with containers (Docker), orchestration (Kubernetes), and Infrastructure as Code.
• Exposure to DevOps, reliability engineering, or production telemetry analysis.
• Prior experience working in AI-powered or data-driven product environments.

Responsibilities

• Design and implement AI-driven quality automation solutions to improve test coverage and defect detection.
• Apply ML/LLM-assisted techniques for test generation, intelligent test selection, prioritization, and regression optimization.
• Build automated quality signals that combine test results, telemetry, logs, and metrics to support data-driven release decisions.
• Drive shift-left and shift-right quality strategies, integrating automation with pre-release pipelines and production monitoring.
• Architect and maintain scalable, modular automation frameworks for API, backend, and system-level testing using Python, Java, or TypeScript.
• Implement automation across distributed systems, microservices, and AI-enabled components.
• Integrate automation into CI/CD pipelines with quality gates and release checks.
• Develop reusable test utilities, data orchestration tools, and environment-aware automation for complex deployments.
• Enable automation reporting and dashboards for engineering, QA, and leadership visibility.
• Design and execute performance, load, and stress testing strategies for cloud-native and distributed systems.
• Establish performance baselines, SLAs/SLOs, and continuously validate system behavior under real-world workloads.
• Analyze performance bottlenecks using observability and APM tools (metrics, logs, traces).
• Collaborate with architecture and DevOps teams to improve scalability, resilience, and system reliability.
• Support production performance validation using telemetry-driven feedback loops.
• Act as a senior technical contributor across Agile Release Trains in a SAFe environment.
• Partner with Product Owners, Architects, and RTEs to embed automation, performance, and quality objectives into PI Planning.
• Contribute to backlog refinement by defining automation and quality enablers.
• Lead root cause analysis for complex quality, performance, and reliability issues across teams.
• Mentor engineers on automation best practices, AI-assisted testing, and quality engineering principles.

Skills

Python

Java

JavaScript/TypeScript

C#

Automation Frameworks

CI/CD Integration

Azure

Microservices

Docker

Kubernetes

Observability

Performance Testing

AI/ML Testing

LLM-assisted testing

Education

BS/MS in Computer Science, Engineering, or related field

Tools

JMeter

Gatling

K6

Docker

Kubernetes

Azure

Job description

The driving force behind our success has always been the people of AspenTech. What drives us, is our aspiration, our desire and ambition to keep pushing the envelope, overcoming any hurdle, challenging the status quo to continually find a better way. You will experience these qualities of passion, pride and aspiration in many ways - from a rich set of career development programs to support of community service projects to social events that foster fun and relationship building across our global community.

The Role We are seeking a Senior Automation and AI-Driven Quality Engineer to design, implement, and scale intelligent quality, automation, and performance engineering solutions across enterprise-grade, AI-enabled platforms. This role is hands‑on and technically deep, with strong ownership across test automation, performance engineering, AI‑assisted quality workflows, and SAFe‑based delivery pipelines. You will work closely with product engineering, architecture, DevOps, and data/AI teams to embed Built‑In Quality into every stage of the SDLC.

Impact

• Design and implement AI‑driven quality automation solutions to improve test coverage & defect detection.
• Apply ML/LLM‑assisted techniques for test generation, intelligent test selection, prioritization, and regression optimization.
• Build automated quality signals that combine test results, telemetry, logs, and metrics to support data‑driven release decisions.
• Drive shift‑left and shift‑right quality strategies, integrating automation with both pre‑release pipelines and production monitoring.
• Architect and maintain scalable, modular automation frameworks for API, backend, and system‑level testing using Python, Java, or TypeScript.
• Implement automation across distributed systems, microservices, and AI‑enabled components.
• Integrate automation into CI/CD pipelines (e.g., Azure DevOps, GitHub Actions, Jenkins) with quality gates and release checks.
• Develop reusable test utilities, data orchestration tools, and environment‑aware automation for complex enterprise deployments.
• Enable automation reporting and dashboards for engineering, QA, and leadership visibility.
• Design and execute performance, load, and stress testing strategies for cloud‑native and distributed systems.
• Establish performance baselines, SLAs/SLOs, and continuously validate system behavior under real‑world workloads.
• Analyze performance bottlenecks using observability and APM tools (metrics, logs, traces).
• Collaborate with architecture and DevOps teams to improve scalability, resilience, and system reliability.
• Support production performance validation using telemetry‑driven feedback loops.
• Act as a senior technical contributor across Agile Release Trains (ARTs) in a SAFe environment.
• Partner with Product Owners, Architects, and RTEs to embed automation, performance, and quality objectives into PI Planning.
• Contribute to backlog refinement by defining automation and quality enablers.
• Lead root cause analysis for complex quality, performance, and reliability issues across teams.
• Mentor engineers on automation best practices, AI‑assisted testing, and quality engineering principles.

What You'll Need

• BS/MS in Computer Science, Engineering, or related field.
• 5+ years of experience in software engineering, with strong focus on automation, quality engineering, or performance engineering.
• Experience with AI/ML‑assisted testing, LLM‑based automation, or intelligent quality systems.
• Strong programming skills in Python, Java, C#, or JavaScript/TypeScript.
• Hands‑on experience building test automation frameworks and integrating them into CI/CD pipelines.
• Experience with cloud platforms (Azure), microservices, and distributed systems.
• Solid understanding of Agile / SAFe delivery models and enterprise‑scale software development.
• Excellent problem‑solving, communication, and cross‑team collaboration skills.
• Familiarity with performance testing tools (e.g., JMeter, Gatling, K6) and observability stacks.
• Experience with containers (Docker), orchestration (Kubernetes), and Infrastructure as Code.
• Exposure to DevOps, reliability engineering, or production telemetry analysis.
• Prior experience working in AI‑powered or data‑driven product environments.

Benefits & Compensation

The salary range for this role is $90,200.00 - $112,800.00. This range represents what we in good faith believe is the range possible for base compensation for this role at the time of this posting. We may ultimately pay more or less than the posted range based on several factors. This range may be modified in the future.

• Additionally, we offer a comprehensive benefits package including paid time off, charitable giveback day, medical/dental/vision insurance, and retirement benefits to eligible employees.
• This role is also eligible for bonus or variable incentive pay.

AspenTech is an Equal Opportunity/Affirmative Action employer. AspenTech does not discriminate against employees or applicants on the basis of age, race, color, religion, creed, ancestry, sex, sexual orientation, gender identity or expression, pregnancy or related conditions, marital status, familial status, national origin, disability, medical condition, genetic information, citizenship, military service or protected Veteran Status or any other basis protected by applicable federal, state, or local law. Reasonable Accommodation: We will provide reasonable accommodations to qualified individuals who have a disability or sincere religious reasons to request accommodation, when necessary to enable the individual to participate in the job application or interview process. If you wish to request an accommodation, please contact us at [e-mail].

GDPR Privacy Notice: AspenTech collects a range of personal information during the recruitment process. This may include the following personal or special categories of personal data: recruitment information such as your application form and resume, references, qualifications and membership of any professional bodies and details of any pre‑employment assessments; your contact details and date of birth; your gender; your marital status and family details; your identification documents including passport and driver's license and information in relation to your immigration status and right to work with us; information about your contract of employment (or services) including start and end dates of employment, role and location, working hours, details of promotion, salary (including details of previous remuneration), pension, benefits, and holiday entitlement; your racial or ethnic origin; any criminal convictions and offences. AspenTech Security and Privacy Policy Plan Participants Enrolled in the AspenTech US Medical Plans: The Transparency in Coverage Final Rules require certain group health plans to disclose on a public website information regarding in‑network provider rates and historical out‑of‑network allowed amounts and billed charges for covered items and services in two separate machine‑readable files (MRF’s). The MRF’s for the benefit package options under AspenTech’s US Employee Benefit Plan are linked below: Transparency in Coverage Rule - Machine Readable Files Transparency In Coverage Rule And Consolidated Appropriations Act Overview and FAQS