About the role Teza is a systematic trading firm developing quantitative strategies across multiple asset classes. We are looking for a Lead Infrastructure Engineer to own the platform that supports our traders, quants, and developers. This includes colocation hardware near the exchanges, research compute and developer services, and the security and release processes that connect these environments. This is a player-coach role. You will lead the infrastructure team, which includes DevOps Engineers and Infrastructure Engineers, and set its technical direction while remaining hands-on. You will provision and tune bare-metal trading servers, respond to production incidents, and review the designs and solutions your team delivers. We are not looking for a manager who delegates all technical work or an engineer who avoids leading people. We need someone who can do both and determine where their time and attention are most needed. Our platform supports active trading and research today, and we are investing in making it more robust, observable, secure, and developer-friendly. You will have significant ownership and decision-making over infrastructure tooling, standards, and priorities across the firm. Location: Austin, Texas (On-Site) What You'll Own: - Trading Infrastructure and Colocation. Oversee server procurement and lifecycle management across multiple exchange colocations. Select low-latency NICs, such as Solarflare, Exanic, and Mellanox, and kernel-bypass technologies. Develop and maintain Linux tuning standards for trading hosts, including CPU isolation, NUMA-aware pinning, IRQ affinity, and BIOS and kernel settings. Manage hardware failures, spare capacity, and capacity planning. - Research and Developer Platform. Oversee compute orchestration for researchers and data engineers, including Slurm for HPC, machine learning, and GPU workloads; Hadoop for batch processing; and Airflow for workflow scheduling. Support shared services such as JupyterHub, databases, artifact storage, and large-dataset storage. Determine when Kubernetes is appropriate and when alternative approaches are better suited. - Security. Establish and maintain access controls for production trading hosts in colocation. Manage network segmentation across colocation, corporate, and research environments. Oversee secrets management for exchange credentials, API keys, and certificates, including rotation, auditing, and deployment integration. Lead vulnerability management, patching for systems that cannot be routinely rebooted, intrusion detection, and incident response. - Releases and Deployment. Define how trading strategies, data pipelines, and real-time trading systems move from development into production. Establish rollback procedures and release processes for infrastructure changes, including kernels, firmware, and NIC drivers. Oversee infrastructure-as-code pipelines and coordinate releases with the trading calendar. - Operational Maturity. Establish the on-call model and escalation paths. Improve observability across internal services through metrics, logging, tracing, and alerting. Lead incident response and blameless post-mortems, ensuring action items are tracked and completed. - Hybrid Infrastructure. Oversee colocation infrastructure for trading, along with on-premises and cloud environments supporting research and corporate workloads. Evaluate the tradeoffs between these environments, manage cloud costs, and establish disaster recovery plans with defined recovery time objectives (RTOs) and recovery point objectives (RPOs). - The Team. Hire, develop, and retain infrastructure engineers. Set priorities across trading performance and latency, research compute needs, and operational tooling. Represent the infrastructure team and its priorities across the firm. What We're Building Toward: These are the shared goals of the infrastructure team. DevOps Engineers and Infrastructure Engineers execute against them, while you set the technical approach, establish priorities, and drive progress. - Full-stack observability across internal services, including unified metrics, centralized logging, distributed tracing, and actionable alerting. - Reliable, self-service compute orchestration across Slurm, Hadoop, and Airflow, enabling researchers and data engineers to run workloads at scale without unnecessary infrastructure bottlenecks. - Mature secrets management for trading credentials, API keys, certificates, and service-to-service authentication, with rotation, auditing, and deployment integration. - Unified release pipelines that standardize how trading strategies, data pipelines, and real-time trading systems move from development to production. - A well-maintained platform foundation that includes identity management, GitHub Actions runners, VPN, and observability tooling, with updates delivered safely and without disrupting active trading. - A strong security posture across production and research environments, with security practices that evolve alongside the platform rather than being added after the fact. Basic Requirements: - Experience operating infrastructure for a trading firm or another environment with strict uptime and latency requirements, including hands-on experience with colocation hardware and bare-metal Linux servers. - Deep, demonstrable expertise in low-latency Linux, including kernel and network tuning, CPU and NUMA isolation, IRQ affinity, and kernel-bypass NICs and technologies such as Solarflare/Onload, Exanic, and Mellanox/DPDK. You must also have the measurement discipline to validate performance improvements. - Experience leading an infrastructure, DevOps, or SRE team, including hiring, setting priorities, and taking accountability for outcomes while remaining a hands-on technical contributor. - Experience building and operating internal platform services for development and research teams, including CI/CD, compute, storage, monitoring, and developer tooling. Experience consuming these services alone is not sufficient. - Strong Linux systems administration skills and experience with container orchestration technologies such as Docker and Kubernetes. You should understand where containers are appropriate in a trading environment and where they are not. - Familiarity with machine learning and data-intensive workflows, including GPU scheduling, large-dataset access patterns, and reproducible compute environments. - Experience designing and operating hybrid infrastructure across colocation, on-premises, and at least one major cloud provider, such as AWS, GCP, or Azure. You should understand the tradeoffs between these environments. - A practical, mature approach to infrastructure security, including access control models such as zero-trust and bastion hosts, network segmentation, secrets management, vulnerability scanning, patch management, audit logging, and incident response. - Hands-on programming experience in Python or another scripting language, with the ability to build tooling, automation, and infrastructure-as-code solutions rather than simply execute existing playbooks. - A solid understanding of core network protocols and services, including TCP/IP, multicast market data delivery, DNS, LDAP, Kerberos, TLS, HTTP, and SSH. - A track record of managing structured on-call and incident response processes, including escalation paths, post-mortems, and follow-through on action items.   Nice to Have: - Experience with FPGA-based or other hardware-accelerated market data and order-entry systems. - Experience with HPC storage and networking, including NFS at scale, parallel filesystems, and InfiniBand. - Familiarity with infrastructure-as-code tools such as Terraform, Pulumi, and Ansible. - Experience with log aggregation and security information and event management (SIEM) systems. - Understanding of compliance frameworks relevant to financial services.   Benefits -  Health, visual and dental insurance -  Flexible sick time policy