[Remote] Cloud Infrastructure Engineer
Note: The job is a remote job and is open to candidates in USA. Teradata is focused on shaping the next generation of its platform through an advanced research team within the Office of the CTO. The Cloud Infrastructure Engineer role is centered on the foundational layer of the system, working on how compute resources are provisioned, configured, and optimized across various environments.
Responsibilities
- Own and evolve how compute infrastructure is provisioned and operates across heterogeneous environments, including bare metal, VMs, containers, and cloud platforms
- Define and tune system-level behavior across CPU, memory, storage, and network, including how workloads are scheduled and resources are utilized
- Design repeatable, auditable provisioning and deployment workflows using infrastructure-as-code tools (e.g., Terraform, Pulumi, or similar)
- Shape runtime characteristics such as startup behavior, workload placement, and resource efficiency as systems scale
- Identify and resolve bottlenecks across I/O throughput, network behavior, and provisioning performance
- Use AI-assisted tools to explore and accelerate implementation, refining outputs into production-ready infrastructure
- Collaborate with control plane engineering to establish a clear and stable foundation for higher-level services
Skills
- Experience working at the systems or infrastructure layer, including OS behavior, runtime environments, or low-level system interactions
- Experience operating Kubernetes (or similar systems), including familiarity with scheduling behavior, node-level characteristics, and cluster lifecycle concerns
- Familiarity with containerization, virtualization, and infrastructure provisioning across cloud and on-premises environments
- Experience designing systems intended to run across multiple environments, with portability and consistency in mind
- Understanding of distributed system behavior, particularly how resource constraints affect performance and scalability
- Experience with observability, profiling, or performance analysis at the system level
- Comfort working in environments where system design and direction are actively evolving
- Hands-on ownership mindset — you take responsibility for how systems behave in production, not just how they're designed on paper
- AI-assisted development fluency — this team uses AI tools as a core part of how work gets done; you're comfortable directing, evaluating, and refining AI-generated implementations
- Clear communication across disciplines — you can explain infrastructure behavior and design tradeoffs to engineers working at higher levels of the stack
- Exposure to query engines, columnar databases, or analytical data platforms (e.g., Presto, Trino, Spark, DataFusion)
- Background in big data infrastructure or data pipelines — familiarity with the scale and volume of data these systems process
- Experience with eBPF, kernel performance tuning, or NUMA-aware hardware configuration
- Contributions to open-source infrastructure tooling
Benefits
- We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work.
- We focus on well-being because we care about our people and their ability to thrive both personally and professionally.
- We are an anti-racist company because our dedication to Diversity, Equity, and Inclusion is more than a statement — it is a deep commitment to doing the work to foster an equitable environment that celebrates people for all of who they are.
Company Overview
Company H1B Sponsorship