Job Title: Principal Automation Engineer (AI)
Deltek is seeking a Principal Automation Engineer with deep expertise in
AI-native test automation to help shape the quality engineering foundation Deltek’s next-generation, AI-first ERP platform for project-based businesses. This is not a role for someone who automates feature regression. It is a role for someone who can harness AI tools to build intelligent automation frameworks that reason, adapt, and self-heal.
You will be the automation architect behind Deltek’s in-house AI-native test automation platform combining Playwright with LLM-powered agents (Planner, Generator, Healer). You will extend, evolve, and industrialize this framework, integrating AI tools at every layer: test generation, self-healing selectors, LLM-as-a-Judge evaluation, and CI/CD-gated quality pipelines.
If you are fluent in
Playwright, agentic AI workflows, and modern test engineering — and want to build something genuinely new rather than maintain legacy frameworks — we invite you to join our team. ERP domain knowledge is a strong plus and will accelerate your impact.
Responsibilities:-
Architect and evolve the AI-native automation framework — extending Playwright-based agents with LLM-powered planning, test generation, and self-healing capabilities.
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Use AI tools extensively (Claude, GitHub Copilot, LLM APIs) to design, generate, and augment automation suites — reducing human authoring effort while increasing scenario coverage.
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Build and maintain Playwright agent pipelines for end-to-end workflow automation across Deltek’s Projects, Workforce Management, and Financials modules.
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Integrate LLM-as-a-Judge (LLMaaJ) evaluation into the test pipeline to automatically score AI-generated outputs, detect hallucinations, and validate response quality against golden datasets.
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Design and implement AI safety and correctness test cases: hallucination detection, bias testing, output guardrail validation, and behavioral consistency across edge cases.
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Own the CI/CD automation pipeline (GitHub Actions / Azure DevOps) for AI-enabled releases — including regression gates, model-response validation, and automated quality dashboards in ReportPortal and Grafana.
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Validate AI/ML outputs including prediction accuracy, recommendation relevance, natural-language responses, and inference API payloads.
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Build and maintain golden datasets for AI drift detection, regression baselines, and LLM evaluation benchmarks.
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Collaborate with Product Managers, AI/ML Engineers, and QE leads to define AI feature release quality gates and automation coverage targets.
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Mentor QE team members on AI-assisted automation patterns, agentic testing concepts, and framework best practices.
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Contribute to test strategy for data migration validation of schema fidelity and record correctness.