Senior Solutions Architect – AI Infrastructure Security (remote in Europe)

Description

The company provides Kubernetes-based AI infrastructure for on-premises, cloud, edge and sovereign data centres, built on open source. Its platform, k0rdent AI, is used to build and run GPU clouds and AI factories, from bare metal up to models.

You will sit in the CTO's office and take ownership of the platform's security design, from firmware through to the models and applications it serves.

Your designs will become published reference architectures, code and proof-of-concept builds that run on real hardware with customers and partners.

Research is central to the role. You will look at threats and designs before customers raise them, prototype ideas that may never ship, and push back on established practice when a better option exists. Your work will shape where the platform goes, not only how it is deployed today.

The job blends research with hands-on, external work. You will design, build and test in the lab, then explain the results to engineers, security teams, executives and conference audiences. You will work with solutions architects, partner management and engineering teams across many countries and time zones.

You will help build the observability foundation for the AI cloud era, working directly with GPU cloud operators, NeoClouds, sovereign clouds and AI-first enterprises, and help shape the product narrative and go-to-market results.

Responsibilities

• Design and publish security reference architectures for single-tenant private AI clouds, multi-tenant GPU clouds and hybrid setups spanning public cloud and on-premises.
• Create a defence-in-depth model covering every layer, from the hardware root of trust and firmware up to hosts, VMs, Kubernetes, networks, storage, models and applications.
• Define tenant isolation boundaries, document where each is strong or weak, and state what it costs to strengthen them.
• Map designs to the controls and frameworks customers must meet, and document trade-offs in risk, cost, performance and operability so customers can follow your reasoning.
• Secure bare-metal hosts: secure and measured boot, TPM attestation, BMC and Redfish hardening, firmware integrity and hardened Linux.
• Secure virtual machines: hypervisor and KubeVirt hardening, VM isolation, and the risks that PCI passthrough and SR-IOV bring for GPUs and NICs.
• Secure Kubernetes: RBAC, Pod Security Standards, admission control, policy-as-code, runtime security and multi-cluster, multi-tenant operation.
• Design secrets management: secret stores, KMS and HSM integration, envelope encryption, delivery to workloads and rotation.
• Design certificates and PKI: internal certificate authorities, automated issuance and rotation, mTLS and workload identity.
• Design network security: segmentation, zero-trust, Kubernetes network policy, tenant isolation on front-end and GPU fabrics, and DPU-based enforcement.
• Design storage security: encryption at rest and in transit, key management, and tenant isolation on shared block, file and object storage holding training data and model weights.
• Cover public cloud security: secure landing zones, identity and access management, network controls, and how these extend into hybrid deployments.
• Define how Transformer-based models are protected across their lifecycle: weight provenance and signing, training and fine-tuning data integrity, and secure model registries.
• Protect inference services and AI applications against prompt injection, data and model exfiltration, model theft and misuse of agentic tool access.
• Design isolation for shared GPU infrastructure using MIG, vGPU and passthrough, and assess confidential computing for models and data in use.
• Secure the software supply chain for platforms, containers and models through image signing, SBOMs, vulnerability management and provenance.
• Track emerging security technologies, standards and threats, including GPU confidential computing, remote attestation, post-quantum cryptography, model signing and AI agent security.
• Prototype alternative designs in the lab, including ones customers have not requested, and benchmark them against current practice.
• Challenge established and customer-preferred designs when the evidence supports a better option, and argue the case with data.
• Publish research notes and design proposals internally, and where suitable, external papers, blog posts and talks.
• Build and run proofs of concept with customers and partners on company lab hardware and on customer sites, and report results against agreed success criteria.
• Write automation, policies and tooling (Python, Go, Bash, Ansible, Helm, Kubernetes manifests, Terraform, policy-as-code) so reference architectures can be reproduced.
• Review designs and deployments through threat modelling, configuration review and hands-on testing, and turn findings into design guidance.
• Act as the security expert in customer discovery, design reviews and architecture workshops, bringing new ideas and not only reflecting current practice.
• Work with customer security, risk and compliance teams, and support security questionnaires and architecture reviews for strategic deals.
• Work with hardware, software and security partners, such as NVIDIA, server OEMs and security vendors, on joint designs and validations.
• Feed research back to product, engineering and the company's security team, and help shape the platform roadmap.
• Present at industry events, webinars and partner summits, and run hands-on workshops for technical audiences.
• Write technical content: reference architectures, solution briefs, blog posts and internal enablement material.

Requirements

• A bachelor's degree in computer science, computer engineering, cybersecurity or a related field, or equivalent practical experience.
• 8+ years in security engineering or security architecture, including at least 3 years securing cloud, Kubernetes or large-scale infrastructure platforms.
• Customer-facing experience as a solutions architect, pre-sales engineer, consultant or technical lead.
• Cloud security: designing and running secure deployments on at least one major public cloud (AWS, Azure or GCP), and on private cloud or bare-metal infrastructure.
• Host and virtualisation security: Linux hardening (for example SELinux, AppArmor or CIS benchmarks), secure boot, TPM, and hypervisor and VM isolation including KubeVirt.
• Kubernetes security: RBAC, Pod Security Standards, admission controllers and policy engines (for example Kyverno or OPA Gatekeeper), runtime security (for example Falco), and multi-tenancy patterns.
• Secrets and key management with tools such as HashiCorp Vault or OpenBao, External Secrets Operator, cloud KMS and HSMs.
• PKI and identity: certificate lifecycle with tools such as cert-manager, mTLS, OIDC, SSO, and workload identity such as SPIFFE/SPIRE.
• Network security: segmentation, firewalling, zero-trust architectures and Kubernetes network policy with tools such as Cilium or Calico.
• Storage and data security: encryption at rest and in transit, key hierarchy design, and access control on shared storage.
• AI security: a working understanding of how Transformer-based models are trained, packaged and served, and of the threats specific to them, such as those in the OWASP Top 10 for LLM Applications and MITRE ATLAS.
• Software supply chain security: image signing (for example Sigstore/cosign), SBOMs, vulnerability scanning and SLSA concepts.
• Programming or scripting in at least one language, Python or Go preferred, and comfort with Git, CI and infrastructure-as-code.
• Curiosity: you dig into how attacks work, read specs, advisories and source code, and track how AI and infrastructure threats change. You question established designs, including those customers are used to.
• Ownership: you take a reference architecture or proof of concept from first sketch to a published, validated result, and stand behind it.
• Initiative: you spot risks and gaps in the product, documentation or a customer design before anyone asks, and act on them.
• Fast learning: you become productive quickly with unfamiliar hardware, software and customer environments.
• Business judgement: you frame security decisions in terms of risk, cost, compliance and time-to-value, and explain them that way to decision makers.
• Excellent written and spoken English, with documents others can build from.
• Comfort presenting to large audiences at conferences and events, and running hands-on workshops.
• Ability to adapt your message from engineers to CISOs and customer executives.
• Experience working in an international, distributed company across time zones and work cultures, with solutions architects, partner management and engineering teams.
• Experience with compliance frameworks and benchmarks for cloud and AI infrastructure, such as NIST SP 800-53, NIST AI RMF, FedRAMP, SOC 2, ISO/IEC 27001, CIS benchmarks or DISA STIGs.
• Hands-on experience with confidential computing (for example AMD SEV-SNP, Intel TDX or NVIDIA GPU confidential computing) and remote attestation.
• Experience securing GPU cloud, neocloud or HPC environments, or NVIDIA Cloud Partner style deployments.
• Experience with DPUs such as NVIDIA BlueField for infrastructure isolation and security offload.
• Offensive security or red-teaming experience, including against AI systems.
• Experience with the company's own products and their security, including its container platform and Kubernetes distribution.
• Security certifications such as CISSP, CCSP, CKS, OSCP or a public cloud security specialty.
• Open-source security or Kubernetes contributions, or a record of public talks and technical writing.
• Participation in standards or industry bodies such as CNCF TAG Security, OpenSSF, Confidential Computing Consortium or CoSAI, or published research, CVEs, patents or white papers.
• Additional languages beyond English.

Conditions

This role is remote and based in the United States, with a strong preference for the East Coast.

You will work with a team spread across many time zones, and some meetings will fall outside standard local hours.

Travel of up to 25% for customer engagements, partner meetings, lab work and industry events, mainly within the US and EU.

Compensation and benefits follow the local market and the employment arrangement.

The company may use automated decision-making technology for certain employment decisions; you may opt out of this for evaluation and review decisions and may appeal any decision it makes.

The company is an equal opportunity employer.