• You’ll be able to tackle high-impact & high-risk projects involving many engineers. • You'll design and implement robust infrastructure systems with a focus on reliability and observability. • You'll maintain our uptime targets while optimizing infrastructure costs. • You'll improve our incident management processes and lead post-mortems. • You'll build and maintain internal tooling (e.g. API, web interface, internal command line, ...) for other engineers. • You’ll have the opportunity to mentor other engineers & lead crews. • You’ll be able to contribute to hiring your future coworkers and shape candidates’ hiring experience (improving our technical assessment process etc...).

• Designing and implementing high-performance data pipelines, APIs, and integrations • Building and maintaining batch and streaming data pipelines using Databricks • Developing and managing inbound/outbound data feeds via APIs, SFTP, pub/sub, or middleware platforms • Building and optimizing data models in Postgres and synchronizing with analytical layers • Collaborating with product, architecture, and InfoSec teams to ensure secure data movement • Implementing data quality, observability, and governance standards • Automating deployment and testing with CI/CD tools • Refactoring existing data pipelines to modern, scalable approaches • Creating build vs buy proposals • Implementing “greenfield” solutions or integrating 3rd party apps

• Build and maintain core AI infrastructure and tooling, including runtimes, model gateways, orchestration layers, and SDKs. • Deliver reusable components that simplify AI development workflows — such as agent orchestration (e.g., LangGraph), vector search (e.g., Weaviate or PGVector), prompt management, and model routing (e.g., LiteLLM). • Work closely with product and infrastructure engineers to solve real pain points, ensuring teams can adopt and scale AI effectively. • Operationalize AI in production by implementing monitoring, evaluation, and fallback systems that keep features reliable and performant. • Drive features from prototype through production rollout, focusing on execution and delivery. • Keep up to date with emerging AI platform tools and frameworks, applying them where they improve team velocity and product reliability. • Share best practices with peers and contribute to building a strong engineering culture on the team.

• Design, build and operate multi-tenant Red Hat OpenShift clusters in enterprise environments • Deploy and manage OpenShift platform services, including: RHACM (Advanced Cluster Management), RHACS (Advanced Cluster Security) • Implement and operate container-native storage solutions:ODF (OpenShift Data Foundation), Ceph (Rook) / NooBaa • Implement GitOps workflows using Argo CD for platform and application lifecycle management • Deploy and manage OpenShift Virtualization for VM-based workloads • Integrate and operate OpenShift AI solutions: Ray / Dask, XGBoost, NVIDIA GPU Operator • Automate platform operations using Ansible Automation Platform (AAP/AWX) • Configure and manage networking components such as MetalLB • Ensure platform stability, scalability, security and compliance • Collaborate with infrastructure, cloud and application teams • Contribute to platform documentation, standards and best practices