ValGenesis

Lead Engineer - DevOps responsible for building and optimizing Azure-based deployment, observability, and cloud operations practices. The role owns reliability, scalability, performance, and sustainability across containerized microservices deployments.

Senior Application Engineer responsible for installing, upgrading, troubleshooting, and maintaining validated enterprise software deployments across customer environments. The role combines technical deployment support, patch development, quality documentation, and guidance for junior team members in regulated life sciences environments.

Test Engineer, Functional responsible for planning, executing, and automating functional, integration, and system testing for regulated enterprise software used in the life sciences industry. The role combines quality assurance, traceability, compliance, and AI-assisted test automation.

Build and deploy production-grade machine learning solutions that improve customer experience and business outcomes in the life sciences industry. This role spans model development, evaluation, GenAI, and real-world ML operations.

Senior Software Engineer focused on building scalable batch and real-time data pipelines, Lakehouse architectures, and production data platforms on Azure. The role also supports ML-ready datasets, analytics, data governance, and operational ML/data workflows.

Site Reliability Engineer responsible for building reliable, observable, and resilient SaaS platforms across Microsoft Azure and on-premises environments. The role focuses on incident response, automation, disaster recovery, performance optimization, and SRE practices.

Senior Software Engineer, R&D focused on researching emerging technologies and turning ideas into prototypes, scalable software, and productized features. The role combines full-stack development with experimentation across modern frontend, cloud, messaging, database, and AI technologies.

Senior Software Engineer focused on building scalable batch and real-time data pipelines, lakehouse architectures, and production data platforms on Azure. The role also supports ML-ready datasets, analytics, governance, and operational ML systems.