Senior QA / QC Engineer to help set the quality bar on a fast-moving mobile product. Testing new features and release candidates across iOS and Android, building and extending test automation in CI/CD, and making release and production checks clear and repeatable.
Compensation
Base salary: €30,400 – €45,600 gross per year (€2,533 – €3,800 gross per month), before employee tax and social-security contributions.
Responsibilities
Build and maintain mobile UI automation (iOS and Android), API test suites and performance and load tests.
Run automated suites in CI/CD against stable test environments.
Build automated regression into each sprint so it runs on every release candidate
Carry out functional and exploratory testing of new work, plus smoke and full regression for each release candidate.
Provide written evidence for release go / no-go decisions.
Design, develop, and maintain high-performance Go backend services for financial and trading platforms.
Responsibilities
Design, develop, maintain, and optimise Go-based applications and backend services for trading platforms, financial analysis tools, and market-related systems.
Build and integrate RESTful APIs and third-party services related to market data, trading systems, and other financial applications.
Optimise application performance, scalability, and reliability in high-volume and low-latency trading environments.
Develop solutions for real-time data ingestion, processing, and analysis, including market data feeds and transactional information.
Build efficient concurrent applications using Go's goroutines, channels, and other concurrency mechanisms.
Digital Forensics Examiner (CELLEX/MEDEX) responsible for conducting digital forensic investigations, deploying to OCONUS locations, and providing technical exploitation services for USSOCOM.
Responsibilities
Leverage deep technical knowledge and a range of forensic tools to exploit digital media and report findings.
Conduct multiple OCONUS deployments per year, including in hostile fire areas, supporting USSOCOM.
Utilize tools like Cellebrite UFED4PC, Physical Analyzer, XRY, AXIOM, X-Ways, FTK Imager, Bulk Extractor, and Autopsy.
Display proficiency with forensic imaging processes and handle various imaging formats and tools.
Understand technical fundamentals of digital forensics, including mobile file systems, operating systems, and encryption.
Requirements
Bachelor’s Degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field. A Master’s Degree may substitute for additional experience.
Nice to have: Bachelor’s Degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field. A Master’s Degree may substitute for additional experience.
The role involves maintaining and optimizing global market data distribution systems that handle real-time, historical, and reference market data for financial instruments with high message volumes and microsecond latency.
Responsibilities
Maintain and optimize global market data distribution systems
Monitor capacity, manage latency, and ensure platform stability and security
Collaborate with users and developers on integration, migrations, and compliance
Support production operations, test new releases, and perform system upgrades
Identify automation and efficiency improvements in daily operations
Requirements
Bachelor's degree in computer science or a related STEM subject (science, technology, engineering, maths)
The AI / ML DevOps Engineer designs, develops, deploys, and supports scalable machine learning solutions that enable advanced analytics and AI capabilities across HonorHealth.
Responsibilities
Design and implementation of the environment that deploys scalable AI/ML solutions, including predictive models, large language model use cases, and agentic workflows that support clinical, operational, and business objectives.
Develops and maintains end-to-end machine learning and RAG pipelines supporting data ingestion, application feature engineering, training, evaluation, deployment, and lifecycle management.
Architects and supports production-grade DevOps practices, including CI/CD, model versioning, automated testing, monitoring, alerting, retraining, and rollback strategies.
Deploys and manages AI/ML applications in cloud environments, ensuring solutions are secure, reliable, performant, and operationally supportable.
Implements observability and performance evaluation practices to manage compute resource utilization, performance, and cost efficiency.