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Lead Automation Engineer – Action; NBA Platform
Job in
Pierre, Hughes County, South Dakota, 57501, USA
Listed on 2026-01-17
Listing for:
Humana Inc
Full Time
position Listed on 2026-01-17
Job specializations:
-
IT/Tech
AI Engineer
Job Description & How to Apply Below
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We are seeking a Lead Automation Engineer to establish and guide a sophisticated quality and test automation function for a large-scale, real-time decisioning platform. This platform delivers personalized recommendations and actions across digital, call-center, and marketing channels through a combination of stateful logic, business rules, and machine learning.
This position extends beyond conventional test automation. You will spearhead the adoption of AI-driven and agentic automation methods to validate intricate decision logic, broaden coverage for edge cases, and enhance system confidence where accuracy, explainability, and reliability are essential.
Key Responsibilities Automation Strategy & Architecture- Develop and own the comprehensive automation strategy for a distributed, real-time decisioning platform, including:
- API and service-level validation
- Stateful workflow and lifecycle testing
- Rules and policy-based logic verification
- Machine learning-assisted ranking and scoring
- Design scalable automation frameworks that support platform growth and continuous integration.
- Lead the implementation of AI-assisted and agentic automation techniques to:
- Generate and refine test cases from API contracts, schemas, and production data
- Automatically explore edge cases through complex state transitions and decision paths
- Minimize test maintenance using self-healing and adaptive automation
- Enhance regression efficiency with intelligent test selection
- Utilize advanced tools such as:
- Large Language Model (LLM)-based test generation and validation
- Agent-driven test execution and environment checks
- AI-supported failure analysis and root cause identification
- Emphasize practical, production-ready AI adoption.
- Build and maintain resilient automation suites to validate:
- Decision accuracy and ranking stability
- State consistency across distributed systems
- Deterministic behavior under diverse conditions
- Fallback and error-handling scenarios
- Develop reusable automation components for adoption by multiple engineering teams.
- Integrate automation processes into CI/CD pipelines for rapid, reliable feedback.
- Ensure automated validation supports:
- Explainability (clarity on decision outcomes)
- Reproducibility (consistent results given identical inputs)
- Auditability (transparent traceability of logic and versions)
- Collaborate with engineering teams to design systems that are testable, observable, and robust.
- Leverage production telemetry and logs to inform and refine automation strategies.
- Serve as the technical leader for automation and quality engineering, establishing standards and best practices.
- Mentor and support automation engineers across teams.
- Partner closely with software, data, and machine learning engineering teams to embed quality early in the development lifecycle.
Required Qualifications
- 8+ years of experience in test automation or quality engineering
- 3+ years in a lead or senior automation engineering role
- Extensive experience testing:
- Distributed systems and real-time APIs
- Stateful and event-driven architectures
- Practical experience with AI-assisted development or automation tools (e.g., LLM-based test/code generation, intelligent debugging, agent-driven workflows)
- Proficiency in one or more modern programming languages (e.g., Java, Python, Type Script)
- Experience testing personalization, recommendation, or decisioning platforms
- Familiarity with rules engines, policy systems, or eligibility logic
- Background in validating machine learning-enabled systems
- Experience in regulated or high-reliability environments
- Automation consistently detects defects in decisioning early and accurately
- Expanded test coverage for complex scenarios with reduced maintenance effort
- Accelerated and more intelligent regression cycles
- Strong engineering confidence in automation results for release decisions
- Platform behavior remains consistent, explainable, and reliable as it scales
Hu…
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