Prime Intellect

Software Engineer

OWN YOUR INTELLIGENCE

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.


ROLE IMPACT

You'll build the systems that turn bare-metal GPU servers into reliable, production-ready compute. Own the machine lifecycle from discovery and provisioning through validation, upgrades, repair, and secure reuse, reducing manual work as our fleet grows.


CORE TECHNICAL RESPONSIBILITIES

 - Build automated discovery, network boot, OS imaging, and configuration workflows for GPU servers

 - Automate BIOS, BMC, NIC, GPU driver, and firmware configuration with staged rollouts and safe recovery paths

 - Develop hardware inventory and lifecycle services that track machine identity, configuration, health, and readiness

 - Create acceptance tests and burn-in workflows for GPUs, memory, storage, and interconnects before capacity enters production

 - Integrate provisioning and health checks with SLURM, Kubernetes, and compute allocation systems

 - Build observability, quarantine, repair, and re-provisioning workflows; partner with datacenter teams to resolve hardware failures

 - Implement secure credential handling, tenant isolation, and data sanitization across the server lifecycle


TECHNICAL REQUIREMENTS


REQUIRED EXPERIENCE

 - 3+ years of experience operating Linux servers or building bare-metal infrastructure automation in production

 - Hands-on experience with PXE/iPXE, DHCP, image provisioning, and out-of-band management such as Redfish or IPMI

 - Strong software engineering and debugging skills in Python, Go, or a comparable language, plus Bash

 - Experience designing reliable automation that handles partial failures, retries, and configuration drift

 - Ability to own operational incidents and collaborate across hardware, networking, and platform teams


INFRASTRUCTURE SKILLS

 - Linux boot, systemd, kernel and driver troubleshooting, and OS image management

 - Infrastructure automation with tools such as Ansible and Terraform

 - GPU server diagnostics, PCIe topology, BMC telemetry, and firmware compatibility

 - Network fundamentals including addressing, VLANs, DNS, and management networks

 - Metrics, logs, alerting, and auditable configuration management


NICE TO HAVE

 - Experience with large NVIDIA GPU fleets, DGX/HGX platforms, or heterogeneous server vendors

 - Experience with MAAS, Ironic, Tinkerbell, or similar provisioning systems

 - Kubernetes or SLURM node lifecycle integrations

 - Hardware qualification, automated burn-in, and fleet health scoring

 - Contributions to open-source infrastructure tooling


GROWTH OPPORTUNITY

You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.

We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.

Apply now and join us in our mission to democratize access to planetary scale computing.


COMPENSATION

Cash compensation range of $150,000–$300,000 plus equity incentives.

Member of Technical Staff - Bare Metal & Fleet Provisioning

Operations

OWN YOUR INTELLIGENCE

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.


ROLE IMPACT

You'll own the operational readiness of the physical infrastructure behind our GPU cloud. Coordinate deployments, hardware maintenance, and incident response with datacenter partners, turning new capacity into dependable production infrastructure and reducing time to repair.


CORE TECHNICAL RESPONSIBILITIES

 - Coordinate rack deployment, cabling, inventory, and acceptance testing for new GPU capacity with datacenter partners and engineering teams

 - Maintain accurate asset records, rack layouts, power allocations, cabling documentation, and spare-parts inventories

 - Lead hardware fault triage and coordinate remote hands, vendor escalations, component replacement, and RMA workflows

 - Establish maintenance plans and change procedures that minimize customer disruption and protect equipment and data

 - Track capacity readiness, hardware failure trends, repair times, and operational risks; automate repetitive reporting and workflows

 - Partner with facility teams on power, cooling, environmental monitoring, and readiness for high-density GPU deployments

 - Create runbooks and escalation procedures and support incident response across datacenter and infrastructure teams


TECHNICAL REQUIREMENTS


REQUIRED EXPERIENCE

 - 3+ years in datacenter operations, hardware infrastructure, or production systems operations

 - Hands-on experience deploying and troubleshooting rack-mounted servers, networking equipment, and structured cabling

 - Experience coordinating datacenter providers, remote hands, and hardware vendors through deployments and incidents

 - Working knowledge of Linux diagnostics, BMC consoles, and server hardware health tools

 - Strong operational judgment, documentation habits, and ownership of issues through resolution


INFRASTRUCTURE SKILLS

 - GPU server components, PCIe devices, memory, storage, and hardware diagnostics

 - Rack power budgeting, redundant power paths, airflow, and high-density cooling fundamentals

 - Fiber and copper cabling, optics, labeling, and physical network troubleshooting

 - Asset tracking, spares management, change control, and incident management

 - Basic scripting for inventory, health checks, and operational automation; familiarity with safe datacenter working practices


NICE TO HAVE

 - Experience with NVIDIA DGX/HGX systems or large GPU cluster deployments

 - Liquid-cooled infrastructure and coordination with facility engineering teams

 - Experience bringing up new datacenter sites or expanding multi-site capacity

 - Hardware qualification, burn-in testing, and reliability analysis

 - Experience integrating physical operations with automated fleet provisioning


GROWTH OPPORTUNITY

You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.

We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.

Apply now and join us in our mission to democratize access to planetary scale computing.


COMPENSATION

Cash compensation range of $150,000–$300,000 plus equity incentives.

Member of Technical Staff - Datacenter Operations

OWN YOUR INTELLIGENCE

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.


ROLE IMPACT

You'll build and operate the storage systems that feed frontier AI workloads. Own reliable, high-throughput access to datasets, checkpoints, and model artifacts, balancing performance, durability, availability, and cost as GPU clusters scale.


CORE TECHNICAL RESPONSIBILITIES

 - Design and operate storage architectures for training datasets, checkpointing, inference artifacts, and shared research workflows

 - Deploy and tune parallel filesystems, object storage, and local NVMe caching for demanding AI workloads

 - Benchmark throughput, latency, metadata performance, and concurrent access with representative training and checkpoint workloads

 - Build provisioning, capacity planning, lifecycle management, and operational automation for storage services

 - Design and test replication, recovery, backup, and failure-handling procedures with explicit durability and availability targets

 - Diagnose performance and reliability issues across applications, clients, networks, filesystems, and devices

 - Implement access controls, tenant separation, quotas, monitoring, and runbooks; collaborate with compute and networking teams


TECHNICAL REQUIREMENTS


REQUIRED EXPERIENCE

 - 3+ years building or operating production distributed storage systems

 - Hands-on experience with at least one parallel or distributed filesystem or object storage platform, such as Lustre, BeeGFS, Ceph, or GPFS

 - Strong Linux administration and performance troubleshooting skills

 - Experience automating infrastructure operations in Python, Go, Bash, or similar languages

 - Understanding of storage failure modes, data integrity, consistency, replication, and recovery


INFRASTRUCTURE SKILLS

 - Block, file, and object storage semantics and their performance tradeoffs

 - NVMe/SSD performance, filesystem tuning, I/O profiling, and benchmarking

 - High-throughput storage networking and distributed client behavior

 - Capacity forecasting, observability, alerting, and safe maintenance procedures

 - Authentication, authorization, encryption, and secure data lifecycle management


NICE TO HAVE

 - Experience supporting large GPU training clusters and high-volume checkpoint workloads

 - S3-compatible object storage, data tiering, or distributed caching

 - RDMA-enabled storage or GPUDirect Storage experience

 - Kubernetes storage integrations or SLURM environments

 - Storage cost optimization and contributions to open-source storage systems


GROWTH OPPORTUNITY

You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.

We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.

Apply now and join us in our mission to democratize access to planetary scale computing.


COMPENSATION

Cash compensation range of $150,000–$300,000 plus equity incentives.

Member of Technical Staff - Storage Infrastructure

OWN YOUR INTELLIGENCE

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.


ROLE IMPACT

You'll design and operate the networks that connect large GPU clusters. Own the reliability and performance of training fabrics, storage networks, and management connectivity so distributed workloads can scale without the network becoming the bottleneck.


CORE TECHNICAL RESPONSIBILITIES

 - Design and deploy scalable datacenter network topologies for GPU training, inference, storage, and management traffic

 - Configure and operate high-performance Ethernet/RoCE and InfiniBand fabrics with clear standards for routing, redundancy, and capacity

 - Automate network provisioning, configuration validation, upgrades, and rollback procedures

 - Diagnose packet loss, congestion, link failures, and collective communication performance across hosts and switches

 - Benchmark end-to-end network performance with infrastructure and ML teams, translating workload needs into measurable acceptance criteria

 - Build monitoring for port health, errors, utilization, congestion, and fabric topology; improve incident response and runbooks

 - Partner with datacenter operators and hardware vendors on cabling, optics, deployment readiness, and failure resolution


TECHNICAL REQUIREMENTS


REQUIRED EXPERIENCE

 - 3+ years of production datacenter networking experience

 - Strong understanding of Ethernet, TCP/IP, routing, switching, and redundant network design

 - Hands-on experience with high-performance GPU networking using InfiniBand or RoCE

 - Experience troubleshooting network problems across Linux hosts, NICs, switches, and physical links

 - Ability to automate network operations with Python, Ansible, or comparable tools


INFRASTRUCTURE SKILLS

 - Leaf-spine architectures, BGP, ECMP, VLANs, and network segmentation

 - RDMA concepts and performance tuning; congestion control and lossless Ethernet considerations

 - Linux networking, NIC drivers and firmware, packet capture, and throughput/latency testing

 - Optics, transceivers, cable management, and link-level diagnostics

 - Safe change management, configuration versioning, telemetry, and alerting


NICE TO HAVE

 - Experience operating 400G/800G networks or large multi-rack GPU clusters

 - NVIDIA Spectrum or Quantum networking experience

 - NCCL performance analysis and distributed training troubleshooting

 - EVPN/VXLAN, SONiC, or network source-of-truth systems

 - Experience with network simulation, automated validation, and capacity planning


GROWTH OPPORTUNITY

You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.

We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.

Apply now and join us in our mission to democratize access to planetary scale computing.


COMPENSATION

Cash compensation range of $150,000–$300,000 plus equity incentives.

Member of Technical Staff - Bare Metal & Fleet Provisioning

Member of Technical Staff - Datacenter Operations

Member of Technical Staff - Storage Infrastructure

Member of Technical Staff - Datacenter Networking