Principal Quality Engineer & AI Quality Archi
2 days ago
Elmwood Park
Job Description ELLKAY started out providing connectivity solutions to laboratories and within a few years, grew to also provide data management solutions to ambulatory organizations. ELLKAY is now a trusted data management partner in five healthcare segments. ELLKAY’s solutions continue to serve laboratories and ambulatory practices and have expanded to empower hospitals and health systems, healthcare IT vendors, ambulatory practices, health plans, and other healthcare organizations with cutting-edge technologies and solutions that drive their growth and interoperability strategies. Today, ELLKAY remains true to our core values, building strong partner relationships and offering unparalleled service and support while providing innovative, scalable solutions to the challenges our customers face in today’s data-rich world. ELLKAY's experience, customer-focused approach, and reputation for innovation, speed, and accuracy differentiate ELLKAY as a premier partner for your interoperability needs and data management strategy. Job Description: The Principal Quality Engineer and AI Quality Architect defines the technical vision, reference architecture, and engineering standards for quality across complex software, data, and AI-enabled products. This hands-on principal role architects scalable automation and evaluation platforms, governs AI-specific quality controls, and guides delivery teams through the highest-risk technical and regulatory decisions. Key responsibilities • Own the enterprise quality engineering and AI assurance architecture, including principles, target-state capabilities, reference patterns, roadmaps, and measurable adoption standards., • Architect modular automation platforms spanning UI, API, contract, integration, event, data, performance, resilience, security, accessibility, and production validation., • Define quality strategies for machine learning, generative AI, agentic workflows, retrieval-augmented generation, and predictive models across training, evaluation, deployment, and monitoring., • Establish AI evaluation frameworks for task correctness, grounding, relevance, hallucination, robustness, bias and fairness, explainability, privacy, toxicity, safety, latency, and cost., • Design representative golden datasets, adversarial suites, synthetic test data, human-review protocols, statistical thresholds, and regression baselines for probabilistic systems., • Validate RAG retrieval quality, prompt and model changes, tool use, agent boundaries, fallback behavior, and defenses against prompt injection, data leakage, and unsafe actions., • Define model and prompt versioning, evaluation gates, lineage, audit evidence, drift detection, observability, rollback criteria, and incident-response patterns., • Embed automated quality controls into CI/CD, MLOps and LLMOps pipelines, cloud platforms, and developer workflows with fast feedback and policy-based release gates., • Set standards for testability, service virtualization, contract testing, environment strategy, test-data management, telemetry, and quality metrics across engineering portfolios., • Lead architecture reviews and proofs of concept; select tools through evidence-based evaluation of scalability, interoperability, security, maintainability, and total cost., • Partner with security, privacy, legal, compliance, clinical, product, data science, and platform leaders to translate regulatory and responsible-AI obligations into verifiable controls., • Coach senior engineers and architects, resolve cross-team technical constraints, and influence investment and platform decisions through clear tradeoff analysis. Required qualifications • Bachelor's or master's degree in computer science, engineering, data science, AI, or a related discipline, or equivalent experience., • Typically 12+ years in software engineering or quality engineering, including enterprise architecture responsibility and recent leadership in AI or ML quality., • Expert-level coding and framework design skills in Python, Java, TypeScript, C#, or comparable languages, with strong API, distributed-system, cloud, CI/CD, and observability expertise., • Deep knowledge of test architecture, reliability engineering, security and privacy testing, data quality, performance engineering, and risk-based release governance., • Hands-on understanding of ML and generative-AI evaluation, RAG systems, embeddings or vector search, model monitoring, probabilistic behavior, and responsible-AI risks., • Ability to define enterprise standards while remaining hands-on with prototypes, reference implementations, design reviews, and complex technical investigations. Preferred qualifications • Experience architecting quality for regulated healthcare platforms and protecting PHI in AI-enabled workflows., • Familiarity with NIST AI RMF, model risk management, healthcare interoperability, and emerging AI governance or regulatory expectations. Benefits: ELLKAY offers a comprehensive and competitive benefit package that starts day one! Including: • Medical, Dental, and Vision benefits, • Employer-paid Life and LTD, • 401k w/ matching – once eligibility is met, • Work/life balance, • Paid Volunteer Program, • Flexible working hours, • Generous FTO, • Remote work options, • Employee Discounts, • Parental Leave Our awesome culture includes: • Working with talented, collaborative, and friendly people who love what they do, • Professional growth within, • Innovation environment, • On site in HQ Free daily lunches