RCH Solutions

Cloud Engineer

• Design and deliver scalable, secure, and compliant cloud solutions supporting life sciences, bioinformatics, and data-intensive workloads.
• Architect and support high-performance computing (HPC) environments, enterprise data platforms, and governed data ecosystems aligned with FAIR principles and regulatory requirements (GxP, GDPR, HIPAA).
• Provide technical leadership across solution lifecycle (design → implementation → optimization).
• Lead technical discovery sessions and design reviews.
• Act as a trusted advisor to clients, guiding them through architecture decisions and industry best practices.
• Promote automation and infrastructure-as-code practices (Terraform, Ansible).

Scientific Computing Cloud Architect

• Design, build, and support solutions on GCP , including services such as BigQuery, BigTable, Cloud Run, Cloud Storage, Pub/Sub, Dataflow, Agent Platform (formerly Vertex Ai), and related cloud-native services.
• Develop and maintain ETL and data pipeline automation for structured and unstructured data workflows.
• Build automation using Python and shell scripting to support workflow execution, data movement, platform integrations, monitoring, and operational tasks.
• Support AI/ML and agent-based workloads including model integration, agent workflows, and AI-enabled automation where applicable.
• Containerize applications, scripts, services, and workflow components using Docker.
• Deploy containerized workloads to cloud-native platforms such as Cloud Run, or other managed GCP runtimes.
• Build and maintain CI/CD pipelines for application deployment, infrastructure changes, workflow automation, and data pipeline releases.
• Develop and maintain Terraform modules for repeatable GCP infrastructure deployments.
• Support and integrate workflow or lab orchestration platforms such as Mendix, NAN, Nextflow, or similar tools.
• Collaborate with application teams, data engineers, lab systems teams, and business stakeholders to translate workflow requirements into scalable cloud solutions.
• Contribute to best practices around cloud security, logging, monitoring, reliability, automation, and cost optimization.

Cloud Engineer – Workflow Automation Specialist

• Design, operate, and continuously improve production-grade K8s clusters at the platform level.
• Lead complex cluster lifecycle management, including:
• Version upgrades and dependency coordination
• Failure recovery and incident resolution
• Non-trivial maintenance and system evolution
• Build and maintain highly reliable, scalable, multi-tenant infrastructure.
• Build and maintain end-to-end observability for LLM-based systems using Grafana, LangFuse, and LangSmith — covering performance, latency, token usage, and alerting.
• Architect and operate shared infrastructure across multiple teams and use cases.
• Implement and enforce RBAC and access control models, Tenant isolation and security boundaries, Resource management and fairness at scale.
• Ensure platform stability under diverse and competing workloads.
• Operate and optimize vector database systems (Weaviate preferred) in production environments.
• Support and scale Retrieval-Augmented Generation (RAG) systems.
• Drive improvements in Query performance and latency, Cluster tuning and resource efficiency, Operational stability of retrieval pipelines.
• Take technical ownership of production systems over time.
• Build and maintain strong practices in Observability (metrics, logs, tracing), Incident response and root cause analysis, Long-term system health and resilience.
• Proactively identify and resolve reliability risks.
• Work closely with backend and GenAI engineers to ensure seamless integration with the platform.

Scientific Computing Cloud Architect

Cloud Engineer – Workflow Automation Specialist

Principal Cloud Platform Engineer