Jobs at Libra Solutions

Coordinates 100–150 active personal injury cases, including medical appointments, treatment, records, transportation, and communication with attorneys, clients, and providers. Evaluates cases and makes funding decisions up to $10,000, maintains workflows, prioritizes tasks, develops professional relationships, supports service and revenue goals, and occasionally trains new team members. The position requires in-office work in Denver, Colorado.

Manage and grow relationships with existing customers (medical providers and attorneys), serve as primary contact for account issues, collaborate with internal teams to improve customer experience, conduct trainings, schedule regular meetings, and drive revenue growth and performance goals.

Own product strategy and execution for C3, an internal case management and operations platform supporting underwriting, servicing, payments, documents, and workflow automation. Lead discovery, prioritization, UX decisions, requirements, engineering collaboration, UAT, AI-assisted product practices, and outcome measurement. Partner with operations, legal, compliance, and go-to-market teams to deliver reliable, scalable capabilities and improve business results.

Designs and maintains automated UI, API, end-to-end, and integration tests across React, Angular, and .NET applications. Validates data flows with SQL Server or Azure SQL, integrates test suites into Azure DevOps quality gates, and manages test data for parallel execution. Uses AI tools to accelerate test generation while critically reviewing coverage and assertion quality. Documents defects in Jira, contributes to test planning and acceptance criteria, and collaborates with engineers and offshore QE teams.

Leads a quality engineering team while remaining hands-on with AI-powered test automation across API, UI, integration, and end-to-end workflows. Evaluates AI tools, improves test frameworks and regression efficiency, supports release readiness, analyzes defects, tracks quality metrics, and partners with Engineering, Product, DevOps, and Release teams. Coaches employees on AI-native quality practices, prompt engineering, responsible AI use, and evaluating AI-generated tests.

Owns end-to-end requirements and delivery for an engineering pod. Leads discovery, authors technical epics and user stories, validates AI-generated requirements, investigates systems via code/DB/API, maintains domain knowledge for AI agents, runs Agile ceremonies, and accepts story delivery through code and acceptance verification.