Cloud Infrastructure Engineer

Join a small advanced research team within the Office of the Chief Technology Officer focused on shaping the next generation of Teradata's platform. This role centers on the foundational layer of the system — how compute actually runs. You'll work close to the hardware and operating system boundary, shaping how resources are provisioned, configured, and optimized across environments spanning bare metal, virtualized systems, containerized platforms, and major cloud providers. Rather than operating within a fixed platform, you will help define how systems behave at runtime. The environments you design are intended to support highly scalable, performance-sensitive workloads, where efficiency, predictability, and resource utilization matter. This is work where resource behavior is not abstract — how scheduling, memory, and I/O interact directly determines whether the system performs or degrades. You'll work with significant ownership in a small team, using AI-assisted development tools to explore, build, and refine systems with the leverage of a much larger organization — while maintaining direct accountability for how those systems perform under real conditions.

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

Requirements

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

Nice to have

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

health care; life and disability insurance; retirement savings (401(k)); time-off programs; annual incentive plans; flexible work model