Job Specifications
Contract: 06 Months Contract (This role will have the opportunity to convert to FTE for the right candidate.)
Location: Indianapolis, IN 46240 Or Portsmouth, NH 03801 Or Boston, MA (MA is the 3rd choice). This role follows a flexible hybrid model (2 days per week in the office). We will consider candidates based in Indianapolis, IN and Portsmouth, NH.
Job Summary:
The GRS Quality Engineering (GRS-QE) organization is seeking a dynamic, hands-on Solutions Engineer to lead and deliver innovative quality-engineering solutions across a large application portfolio. Your focus will be Gen-AI–driven enterprise test automation, quality insights, performance engineering, data-validation frameworks, and tight collaboration with Site Reliability Engineering to build observability into every stage of the SDLC. You’ll combine deep technical expertise with strong leadership to architect, implement, and scale modern testing platforms that enable teams worldwide to ship faster and safer.
HM Notes:
This is an architect-level testing role requiring both technical leadership and hands-on expertise.
Ability to design and drive overall test strategy.
Focuses on proactively identifying issues, tracking metrics, and responding based on data insights.
Requires performance engineering experience using tools like LoadRunner or K6.
Hands-on experience with data validation using SQL.
Background in AWS cloud environments.
Familiarity with containerization technologies (Docker or Kubernetes).
Exposure to or working knowledge of AI/LLM technologies.
Interview Process: Consists of two rounds: the first with Mark, followed by a panel interview.
Required:
This is a combo role, looking for a Leader + Test Engineer + Architect to support the modernization of few hundred systems over a few years. Need solid stakeholder communication skills and some experience with AI. Must be comfortable using tools like Copilot, ChatGPT, etc. Looking for someone who understands testing but can also do technical as well as validating data in a database.
We encourage you to apply if you are a:
Strategic Partner – able to connect the dots between business outcomes, customer experience, and technical architecture.
Proficient Communicator – able to effectively communicate to multiple levels of org leadership
Systems-Level Engineer – comfortable whiteboarding end-to-end flows for microservices, event buses, data contracts, and test hooks—knowing where the risks live.
AI-Curious Practitioner – always exploring Gen-AI, ML, and autonomous testing trends, turning hype into production value.
Change Agent – skilled at leading by influence, facilitating consensus across dev, ops, product, SRE, and leadership stakeholders.
Mentor & Multiplier – committed to raising the bar for everyone around you through coaching, pairing, and knowledge sharing.
Core Qualifications:
Bachelor’s or master’s degree in computer science, Engineering, or a related discipline (or equivalent experience).
10+ years of hands-on software or quality engineering experience with demonstrated technical leadership.
Proven expertise in building and integrating large-scale test automation frameworks within AWS environments.
Hands-on skills with at least two of the following: Playwright, UiPath, Rest Assured, Postman, Pact.
Experience embedding automated tests into CI/CD pipelines using GitHub Actions, Azure DevOps, or similar.
Solid understanding of cloud-native architectures, microservices, containerization (Docker/Kubernetes), and infrastructure-as-code.
Familiarity with performance/load testing tools (k6, JMeter, LoadRunner) and observability platforms (DataDog).
Exposure to Gen-AI/LLM-powered testing tools (Copilot, OpenAI) or custom prompt/embedding solutions.
Strong communication, facilitation, consensus-building, and stakeholder-management skills.
Proven ability to mentor and elevate team technical capabilities.
Relevant certifications (AWS, testing tools, or observability) are a plus.
Duties and Responsibilities:
Lead the end-to-end delivery of quality-engineering solutions that meet customer needs while aligning with technology guardrails and strategic roadmaps.
Partner with Site Reliability Engineering (SRE) to embed observability—metrics, logs, traces—into automated tests and quality gates, reducing MTTR and boosting incident readiness.
Drive Gen-AI/LLM experimentation (self-healing tests, autonomous test-case generation, AI-assisted defect triage) and transition validated prototypes into production platforms.
Guide feature teams on modern quality practices: Shift-Left, DevTestOps, contract testing, performance engineering, data validation, and program-level quality governance.
Integrate and optimize vendor testing platforms/tools (e.g., PractiTest, Lambda Test, LoadRunner, UiPath) to maximize business value and ROI.
Collaborate with product managers, architects, engineers, and business stakeholders to translate requirements into scalable quality solutions, and quality solutions into