Senior AI Systems Quality Engineer

🕒 Maio 18

🍂 Massachusetts – Remoto

🍂 Massachusetts – Remote

⏰ Tempo Integral

🟠 Sênior

🔧 Engenheiro de QA (Qualidade de Software)

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Abacus Insights

SiteLinkedInTodas as Vagas

51 - 200 funcionários

⚕️ Seguro de Saúde

☁️ SaaS

Healthcare Insurance • SaaS • Data Management

A Abacus Insights é uma líder em soluções de dados para planos de saúde que capacita os pagadores de saúde, fornecendo dados utilizáveis e interoperáveis. A empresa oferece um conjunto abrangente de soluções de dados projetadas para atender a complexos mandatos governamentais e melhorar a prontidão dos pagadores. A plataforma da Abacus Insights é capaz de consolidar e normalizar diversas fontes de dados em registros de pacientes completos, garantindo a precisão dos dados e facilitando atualizações rápidas. Suas soluções suportam múltiplos casos de uso, incluindo ajuste de riscos, troca de dados clínicos, gestão de custos e relatórios de desempenho. Com foco em tecnologia e saúde, a Abacus Insights ajuda os pagadores a gerenciar custos e melhorar a experiência dos membros através de capacidades aprimoradas de gerenciamento de dados.

Descrição

• Build and ship production-grade, automated validation frameworks, test harnesses, and evaluation pipelines across the AI lifecycle (design → deploy). • Design and evolve an AI testing platform integrated with Databricks and MLflow, enabling repeatable testing, traceability, and auditability. • Create large-scale, scenario-based test suites (hundreds to thousands of cases) to validate agentic workflows end-to-end, including edge cases, long-tail scenarios, and failure modes. • Validate orchestration behavior (tool use, memory, decision logic) and stress-test non-deterministic system behavior before production. • Embed quality by design: define system contracts, guardrails, and safe-degradation patterns at key boundaries. • Define measurable quality signals for LLM systems (grounding, hallucinations, relevance, latency, cost) and integrate them into CI/CD pipelines as automated quality gates. • Ensure AI validation runs automatically on model, prompt, and code changes—enabling continuous quality enforcement. • Build reusable libraries and components so teams can adopt consistent AI quality practices quickly. • Own aspects of AI release readiness, including defining go/no-go criteria based on measurable quality thresholds. • Partner with AI, platform, security, and delivery teams to translate mission needs into clear quality criteria, tradeoffs, and confidence levels.

🎯 Requisitos

• 7+ years of software engineering experience, primarily in backend or platform systems. • Proven experience designing and implementing AI testing automation in production environments, not just executing tests. • Demonstrated ability to build custom validation, evaluation, or testing frameworks for complex, distributed systems. • Strong proficiency in Python and/or TypeScript within modern AI engineering stacks. • Hands-on experience with AI-powered systems, including LLM-based or agentic workflows and non-deterministic behavior. • Experience designing or contributing to AI testing at scale, including regression frameworks, long-tail evaluation, and large test coverage. • Deep understanding of CI/CD integration, including embedding automated tests and quality gates into deployment pipelines. • Solid understanding of AWS cloud-native architectures. • Track record of engineering for quality, reliability, governance, and safety as core system design principles. • Working knowledge of security, privacy, and operational risk in regulated or mission-critical environments, including failure modes and recovery. • Experience with AI testing methodologies, including evaluation of non-deterministic outputs, drift detection, bias/fairness testing, and robust regression strategies. • Proven ability to establish measurable trust thresholds for AI systems, including defining and operationalizing success metrics such as query accuracy, hallucination limits, explainability, and PHI-safe behavior as enforceable release criteria. • Experience working with domain experts to define correctness and real-world validation scenarios, enabling large-scale, business-relevant test coverage that reflects true production use cases rather than engineering-only perspectives.

🏖️ Benefícios

• Unlimited paid time off – recharge when you need it • Work from anywhere – flexibility to fit your life • Comprehensive health coverage – multiple plan options to choose from • Equity for every employee – share in our success • Growth-focused environment – your development matters here • Home office setup allowance – one-time support to get you started • Monthly cell phone allowance – stay connected with ease