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We are looking for an AI Quality & Evaluation Engineer to own the quality planning and execution of an AI-powered chat application operating over complex law enforcement and mobile device data.
This is a highly hands-on role focused on execution rather than high-level QA strategy. You will design, build, and run automated and semi-automated tests for LLM-driven workflows, create evaluation datasets, and continuously stress the system with realistic and extreme investigative scenarios.
What you will be doing:
Design, plan, and execute quality tests for an AI chat application built on LLMs and investigative data.
Build and maintain automation frameworks for prompt regression testing, multi-turn conversations, and model upgrades.
Create and curate evaluation datasets used for regression testing, benchmarking, and model comparison.
Design complex investigative scenarios including ambiguous, incomplete, or conflicting datasets.
Execute manual exploratory testing to uncover hallucinations, reasoning failures, and edge cases.
Work closely with engineering, product, and data teams as part of the development lifecycle.
Validate release readiness and identify regressions related to prompts, models, or data pipelines.
What makes this role different:
You are evaluating AI behavior rather than fixed expected outputs.
You help define what correctness and quality mean for AI reasoning over sensitive data.
You actively invent scenarios to stretch and break the system.
Your work directly impacts trust, reliability, and investigative confidence.

We are seeking a QA Engineer with a strong passion for data quality, performance, and scale to join our Data Platform team.
This role is ideal for a QA professional who enjoys working close to complex data systems, understands large-scale pipelines, and wants to play a key role in shaping the automation and quality strategy of a data engineering organization.
You will act as the primary quality owner for high-volume, mission-critical data platforms, working closely with data engineers, backend developers, and platform teams.
What Youll Do:
Data Quality & Validation:
Design and execute data validation strategies for large-scale batch and streaming pipelines
Ensure data correctness, completeness, freshness, and consistency across the data lake
Define and automate checks for schema changes, data drift, and data quality regressions
Performance & Scalability Testing:
Plan and execute performance and scalability tests for data pipelines and processing jobs
Identify bottlenecks across ingestion, transformation, and querying layers
Partner with engineers to validate performance improvements and prevent regressions
Automation & Infrastructure:
Develop and maintain the data teams QA automation infrastructure
Build reusable testing frameworks and tools tailored for large datasets and pipelines
Integrate automated tests into CI/CD pipelines and production monitoring workflows
Collaboration & Ownership:
Work closely with data engineers, backend developers, and platform engineers throughout the development lifecycle
Act as the sole QA owner within a cross-functional team, driving quality without becoming a bottleneck
Participate in design discussions to ensure testability and observability are built in from the start
Quality Mindset & Communication:
Champion a quality-first culture within the team
Clearly communicate risks, findings, and quality metrics to technical stakeholders
Balance thoroughness with pragmatism in fast-moving, high-scale environments.

hiring a QA Engineer that will join our Engineering department and contribute significantly to the testing of our next-generation products. This position requires a talented software engineer who possesses the drive to explore new technologies and a commitment to maintaining high standards of excellence.

Your Responsibilities
Play a key role in quality assurance processes across all phases of the lifecycle: design, development, integration, release, and deployment.

Ensure project goals, schedules, and quality objectives are consistently met.

Provide detailed test results and product feedback to facilitate continuous process and product improvements.