AI Quality Engineer

Working at Allegis Global Solutions (AGS) is more than just a job. It’s a career. It’s a community of people who invest in your development and empower you to blaze your own trail. Each of us is here to create real, measurable impact that moves needles. We operate beyond "roles" or "jobs" to realize the opportunity to make meaningful contributions to a bigger idea. Because we believe that when you build a workforce that’s designed to harness human enterprise, you design a workforce that’s built for impact.

At AGS, we help companies all over the world transform their people into a competitive advantage. It’s not about filling seats. It’s about designing workforces to meet missions and unleash the most transformative power in business today: The power of human enterprise.

With services around the globe, we have a point of view on the future of work that enables us to be a transformative partner in the way work gets done for our clients’ organizations. Meeting clients where they are, we design a plan and guide them along a transformational journey, applying bold actions and diverse minds to solve the most complex challenges – from permanent and extended workforce management to services procurement, consulting, direct sourcing and our Universal Workforce Model™.

We also represent over 100 countries and speak dozens of languages. So as you’re building relationships and doing your job, you’ll be exposed to other cultures and advancement opportunities while expanding your knowledge of global markets and strategies.

As a workplace, we focus on relationships – with each other, our clients and our candidates - in fact serving others is one of our core values. We support open communication and recognize that giving constructive criticism can be even harder than receiving it. We appreciate the fearless and the passionate, who force us to be better. Everything we do sits on a pillar of diversity - diverse perspectives, backgrounds and ideas drive innovation and make us successful.

See what it’s like to work at AGS by searching #LifeAtAGS on any social network.

Job Description

About the Role

Testing AI systems is a fundamentally different problem than testing traditional software. Outputs are non-deterministic. "Correct" is often a spectrum. And the failure modes—hallucinations, drift, prompt injection—don't show up in unit tests. We need an engineer who understands this and can build the testing strategies, evaluation frameworks, and quality infrastructure to keep our agents reliable in production.

As an AI Quality Engineer, you'll design how we test intelligent agents, agentic workflows, and Foundation Layer capabilities. This is not a manual QA role—you'll write code, build evaluation pipelines, and create automated testing frameworks that run in CI/CD. You'll define what "quality" means for AI systems at AGS and build the systems to measure it.

You'll work across every solution the team builds, which means you'll have broad visibility into the architecture and deep understanding of how our agents behave in the real world. If you're an engineer who cares about quality and wants to solve testing problems that most teams haven't figured out yet, this is the role.

Responsibilities

Testing Strategy & Design
Define testing strategies for AI agents, conversational interfaces, and agentic workflows
Design behavioral test suites for non-deterministic outputs—where "correct" isn't binary
Build evaluation frameworks that measure groundedness, factuality, relevance, and task completion
Identify failure modes specific to AI systems: hallucinations, prompt injection, context window limitations, drift
Develop testing approaches for each architecture pattern: RAG, function calling, human-in-the-loop, autonomous workflows
Test Automation & Infrastructure
Build automated evaluation pipelines that run as part of CI/CD
Create test harnesses for LLM-based systems—mocking, fixtures, and reproducible test scenarios
Develop regression suites that detect quality degradation when prompts, models, or data change
Build monitoring and alerting for production agent quality (accuracy, latency, error rates)
Maintain test infrastructure: test data management, environment setup, reporting dashboards
Evaluation & Metrics
Define quality metrics for each solution—what to measure and what thresholds matter
Build and maintain evaluation datasets (ground truth, reference outputs, edge case collections)
Conduct systematic prompt evaluation when prompts or models change
Track quality trends over time and identify when re-evaluation is needed
Report quality metrics to the team and stakeholders in clear, actionable terms
Collaboration & Quality Culture
Partner with AI Solutions Engineers to define testability requirements during design
Work with AI Solutions Analysts to translate acceptance criteria into test scenarios
Review solution designs from a quality and testability perspective
Advocate for quality practices across the team—testing isn't an afterthought, it's part of delivery
Contribute to incident response by diagnosing quality failures and building regression tests

Qualifications

Qualifications

Required

• 3–7 years of software engineering or quality engineering experience
• Strong programming skills in Python and/or TypeScript—you write test code, not just test cases
• Experience designing and building automated test frameworks
• Understanding of AI/ML systems—you know why testing LLM outputs is different from testing deterministic code
• Experience with CI/CD pipelines and integrating automated tests into build processes
• Ability to reason about non-deterministic systems and design meaningful quality metrics
• Strong analytical skills—you can look at agent outputs and determine whether they're good enough

Preferred

• Experience testing AI/ML applications, conversational interfaces, or chatbots
• Background in LLM evaluation: prompt testing, groundedness scoring, factuality checking
• Familiarity with evaluation frameworks (DeepEval, Ragas, custom evaluation pipelines)
• Experience with Microsoft Power Platform (Power Automate, Copilot Studio) testing
• Background in Azure services and cloud-based test infrastructure
• Experience with load testing and performance testing for API-based systems
• Familiarity with staffing, HR tech, or workforce management domains

Technology Stack

Languages: Python, TypeScript

• Platforms: Azure (Container Apps, Functions, AI Services), Microsoft 365
• Testing: pytest, evaluation frameworks (DeepEval, Ragas, custom), load testing tools
• AI/ML: LLM evaluation, prompt testing, RAG evaluation, behavioral testing

Data: REST APIs, Dataverse, SQL

Tools: Git, GitHub, CI/CD pipelines, Docker, monitoring/alerting (Application Insights)

We don't expect expertise in everything. AI quality engineering is a new discipline—we expect strong engineering fundamentals and the ability to figure out new problems.

What We're NOT Looking For

Manual testers who write test cases in spreadsheets
QA professionals who treat testing as a gate at the end of development rather than a practice woven into it
People who expect deterministic pass/fail for every test—AI quality requires nuance
Engineers who test to the spec but don't think about how real users will break things

What Makes You Stand Out

You've tested a system where "correct" was hard to define—and found a way to measure it anyway
You write test code that's as clean and maintainable as production code
You think about edge cases that nobody else considers
You can explain why a particular quality metric matters and what threshold makes sense
You've built test automation that actually caught regressions before they hit production
You're comfortable saying "this isn't good enough" and backing it up with data

What We're Building

The AI Engineering team delivers intelligent solutions for AGS's global clients

Intelligent Agents — Conversational AI that helps hiring managers, recruiters, and internal teams get work done faster

Agentic Workflows — Automated processes where AI executes tasks with human oversight

Foundation Capabilities — Reusable AI services that power multiple solutions

You'll make sure these systems work reliably—not just at launch, but as models change, data evolves, and usage scales.

Career Growth

AI quality engineering is an emerging discipline with no ceiling. Growth paths include

Depth — Become the team's authority on AI evaluation and testing methodology, influencing quality standards across the organization
Breadth — Move into a Senior or Lead AI Solutions Engineer role, bringing your quality mindset to architecture and delivery
Specialization — Build expertise in areas like LLM security testing, AI safety, or evaluation research

Additional Information

As a workplace, we focus on relationships – with each other, our clients and our candidates - in fact serving others is one of our core values. We support open communication and recognize that giving constructive criticism can be even harder than receiving it. We appreciate the fearless and the passionate, who force us to be better. Everything we do sits on a pillar of diversity - diverse perspectives, backgrounds and ideas drive innovation and make us successful.

See what it’s like to work at AGS by searching #LifeAtAGS on any social network.