Jobs at Experity

Develops software applications incorporating artificial intelligence. The provided description contains no further responsibilities, qualifications, technologies, compensation, travel, sponsorship, or clearance details.

Own analytical domains and build production-grade semantic models, governed metrics, reusable datasets, and AI-ready data products. Translate ambiguous requirements into scalable solutions using SQL, Python, Snowflake, and dbt. Establish testing, documentation, monitoring, and data-quality controls while partnering with analytics, engineering, product, architecture, and business teams. Review designs, troubleshoot production issues, define reusable patterns, and mentor engineers.

Leads and develops a data engineering team while owning scalable cloud data platforms, pipelines, reliability, governance, security, and delivery execution. Partners with Product, Analytics, AI/ML, Security, and architecture stakeholders to modernize data infrastructure, improve quality and observability, manage costs, and enable trusted analytics and AI-ready data products. Requires strong technical engagement in SQL, Python, cloud platforms, distributed processing, and modern DataOps practices alongside people management.

Leads architecture and development of Experity’s RCM automation platform, including backend services, APIs, integrations, workflows, business rules, data, and AI-enabled capabilities. Designs resilient distributed systems, mentors engineers, establishes reusable technical standards, and guides cross-team technical decisions. Builds secure, observable healthcare transaction systems supporting claims, payments, denials, and exceptions while balancing deterministic software, rules, machine learning, and AI agents.

Build and architect production REST APIs, domain-driven services, and healthcare application features across desktop and web platforms. Develop real-time and event-driven capabilities, integrate AWS services, and maintain CI/CD pipelines. Own testing, authentication, observability, resilience, and security practices. Collaborate with platform and security teams while mentoring engineers through code reviews and pairing. Over time, take ownership of service domains or desktop features and contribute to architecture and quality improvements.

Owns execution of data and analytics product roadmaps from discovery through delivery and adoption. Responsibilities include backlog prioritization, requirements definition, acceptance criteria, stakeholder coordination, documentation, scope management, and monitoring product performance. The role partners with Product, Data Engineering, Analytics, Architecture, QA, customers, and business teams to deliver trusted, scalable data capabilities.

Own analytical domains and build scalable semantic models, governed metrics, reusable datasets, and AI-ready data products. Develop production-quality SQL and Python transformations using Snowflake and dbt, with automated testing, documentation, monitoring, and data-quality controls. Translate ambiguous requirements into trusted analytical foundations, collaborate with cross-functional teams, review designs and code, troubleshoot production issues, and establish reusable engineering patterns while mentoring other engineers.

Design, develop, maintain, and support custom .NET applications across frontend and backend systems. Write maintainable code, troubleshoot issues, participate in code reviews and Agile ceremonies, and collaborate on system requirements and design. Build RESTful APIs and microservices using ASP.NET Core, apply software design patterns and domain-driven design, and work with relational databases, ORM frameworks, testing tools, cloud or on-premises environments, and Docker.

Design, develop, maintain, and support custom .NET applications across frontend and backend systems. Write maintainable code, apply software development lifecycle standards, collaborate on requirements and design, troubleshoot issues, participate in code reviews and Agile ceremonies, and improve development practices. The role requires experience with C#, ASP.NET Core, TypeScript, WPF, APIs, microservices, databases, testing, cloud or on-premises environments, and Docker.

Leads the design, administration, optimization, security, and reliability of PostgreSQL and MySQL databases on AWS RDS and Aurora. Responsibilities include high availability, replication, performance tuning, backup and recovery, monitoring, cost optimization, automation, migrations, incident response, and disaster recovery. Partners with engineering and infrastructure teams, mentors colleagues, and drives database observability and operational excellence for high-volume SaaS workloads.

Own analytical domains and build scalable semantic models, governed metrics, reusable datasets, and AI-ready data products. Translate ambiguous business needs into production-quality solutions using SQL, Python, Snowflake, and dbt. Establish testing, documentation, monitoring, and data-quality controls while partnering with analytics, engineering, product, architecture, and business teams. Review designs, troubleshoot production issues, define reusable patterns, and mentor less-experienced engineers.

Hands-on software architect responsible for diagnosing a legacy Windows/WPF EMR, debugging multithreaded C# and real-time data flows, defining domain boundaries, and creating visual architecture diagrams and a phased migration roadmap to a modular modern web stack. The role balances immediate stabilization with long-term modernization and communicates technical tradeoffs to engineers and executives.

Leads a cross-functional engineering and quality POD, overseeing delivery execution, team health, software quality, operational stability, and talent development. Partners with Product Management and Architecture to translate roadmaps into executable plans, manage dependencies and risks, improve Agile and release practices, and monitor delivery metrics. Drives AI-assisted engineering and test automation adoption while maintaining security, compliance, and code quality. Supports hiring, onboarding, succession planning, and cross-team delivery standardization.

The job description provides no role-specific responsibilities or qualifications beyond the senior Machine Learning Engineer title. The employer includes an equal opportunity statement and directs applicants to federal employment rights information.

Lead design and implementation of scalable test automation and quality strategies. Develop automated tests for web, API, and backend services, integrate tests into CI/CD, mentor engineers, and drive quality improvements across the SDLC.

The job description provides no specific responsibilities or qualifications beyond the Software Test Engineer II title. The role likely involves testing software, but no further details are provided.

Lead design and execution of performance testing strategies for web, mobile, API, and distributed systems. Develop automated test scripts, integrate tests into CI/CD, analyze performance metrics, identify bottlenecks, recommend optimizations, and mentor engineers. Validate cloud-native scalability and resilience using observability tools and performance quality gates.

Senior Software Engineer role with no specific responsibilities, qualifications, technologies, compensation, travel, sponsorship, or clearance details provided.

The job description provides no specific responsibilities or qualifications beyond identifying the position as a Data Analyst.

Develop and maintain Java platform software. The provided description contains no additional responsibilities or role-specific details.