AI SDET- Data

Ensora Health

About The Position

Ensora Health is seeking an AI Software Development Engineer in Test (SDET) to ensure the quality, reliability, and trustworthiness of AI‑powered applications. This role is automation‑first and focuses heavily on validating AI behavior, verifying data correctness, and ensuring system reliability across backend services, data pipelines, Retrieval‑Augmented Generation (RAG) systems, and AI agents. You will work closely with AI, machine learning, data, and platform engineering teams, with guidance and support from senior quality leadership.

Requirements

Strong experience as an SDET or Automation Engineer with a focus on backend and service‑level testing
Proficiency in test automation using one or more programming languages (TypeScript, Java, C#, or Python)
Strong experience with API testing and distributed systems validation
Solid understanding of data validation concepts including accuracy, consistency, and completeness
Strong SQL skills
Hands‑on experience using SQL and/or programmatic checks to validate data used by applications or AI systems
Experience integrating automated tests into CI/CD pipelines
Ability to translate requirements and expected AI behavior into reliable, repeatable automated tests

Nice To Haves

Experience testing AI/ML systems, RAG pipelines, or LLM‑based applications
Familiarity with testing non‑deterministic systems and defining effective test oracles
Experience validating data drift, model regressions, or AI behavior changes over time
Familiarity with Playwright, Postman, or similar testing frameworks
Experience working with data‑intensive platforms or analytics systems
Background in healthcare or other regulated environments
Interest in leveraging AI‑assisted testing techniques to improve coverage and efficiency

Responsibilities

Design, build, and maintain robust automated tests for backend services, APIs, and AI‑enabled systems
Validate end‑to‑end AI workflows, including data inputs, retrieval logic, and generated outputs
Test RAG systems by verifying source data quality, retrieval accuracy, and response correctness
Perform data verification to ensure the accuracy of summarized, derived, and feature‑level data used by AI systems
Validate AI behavior for consistency, edge cases, regressions, and failure scenarios
Identify data anomalies, drift, and pipeline issues impacting AI outputs and collaborate on resolution
Integrate automated tests into CI/CD pipelines and contribute to quality metrics and reporting
Support performance, reliability, and scalability testing for AI‑driven services