Staff Engineer, Software Distribution onPrem

Hyperproof; Paris (TX); On-site; USD 101,000 - 146,000; Full time

Benefits offered by this job

Equity and early ownership

Paris office / flexible location

Job summary

Qevlar AI is hiring for an on-premise security software engineer to deploy an AI-driven platform inside customer datacentres. You will own the reference architecture, dependencies, and the entire self-hosted bundle for air-gapped setups.

You will lead the replacement of cloud services with self-hosted equivalents, manage GPU serving stacks, and build a robust test harness to make releases boring. Bilingual French/English is required.

Qualifications

• Shipped software that others install (on-prem experiences preferred).
• Deep Helm expertise: subcharts, templating, values design; OCI registries; Kubernetes beyond a single distribution.
• Experience in air-gapped environments: image mirroring, offline bundles, egress proxies.
• Experience replacing cloud services with self-hosted equivalents (Postgres operators, S3-compatible storage, Vault).
• Strong Go and/or Python; infra-as-code with Terraform, Ansible, CI.
• Experience serving models on GPU with VRAM sizing and model distribution.
• Fluent in French and English.

Responsibilities

• Decide what to port and draft the on-prem reference architecture with explicit dependencies.
• Ship the bundle: Helm chart and an air-gapped tarball for vanilla Kubernetes and OpenShift.
• Replace cloud components with self-hosted equivalents behind clean abstractions.
• Size the inference layer; manage VRAM, concurrency, and weight distribution across air gap.
• Build a test harness for releases with ephemeral environments and smoke tests.
• Ensure signed images, SBOMs, minimal base images with no CVEs at release.
• Impose upgrade contracts across the org with backward-compatible migrations and feature flags.
• Keep the product simple and avoid new unmanaged dependencies.

Job description

About Qevlar AI

Qevlar is a B2B SaaS scale-up on a mission to boost the productivity of cybersecurity teams with Artificial Intelligence. We build an AI platform that transitions Security Operations Centers from reactive to proactive units through autonomous security alert investigations.

In just three years, we have:

• Raised a total of $44m in series-A & seed rounds from EQT Ventures, Forgepoint Capital and Partech

• Deployed our solution with major Enterprises such as Sodexo and GlobalConnect, and leading MSSPs like Orange Cyberdefense

• Expanded to the US market with a growing North American presence

• Ended 2025 with a strong multi-million dollar ARR and ambitious goals for 2026

We are launching Qevlar on-premise for customers who cannot let their security data leave their perimeter. Your job is to turn a signed bundle into a running production platform inside their datacentre, and to make each deployment faster than the last.

On these accounts the critical path is rarely the software. It is the security review board, the firewall change request, the PKI team, the change advisory board. Someone has to own that path, with enough technical credibility to be taken seriously by the customer's infrastructure architects: this is your role.

What You Will do

• Decide what we do not port. Your first deliverable is the on-prem reference architecture and the explicit list of dependencies, services and features that will not cross the boundary. You will hold that line against the rest of engineering, with our backing.

• Ship the bundle. A Helm chart and an air-gapped tarball that install on vanilla Kubernetes and on OpenShift, with no internet access, in under four hours — by someone who has never seen our code and has only your documentation.

• Replace the cloud underneath us. Self-hosted Postgres, S3-compatible object storage, secret management, identity federation — behind abstractions clean enough that we never fork the product or let on-prem drift away from SaaS.

• Package and size the inference layer. Our platform runs agentic investigations, which means sustained LLM throughput. You own the serving stack in the bundle, the VRAM and concurrency sizing matrix customers use to provision their own GPUs, and the distribution and rollback of model weights across an air gap.

• Build the test harness that makes releases boring. Ephemeral customer-shaped environments, install and upgrade smoke tests across Kubernetes distributions, identity providers and network modes — until validating a release candidate takes a day, not a week.

• Ship clean. Signed images, SBOMs, minimal base images, no critical or high CVEs at release. Our buyers are security teams; they will scan everything we hand them on day one.

• Impose the upgrade contract on the whole org. Tested N-3 upgrade paths, backward-compatible migrations, no feature merged without a feature flag, a health check and a support-bundle contribution. Customers will jump from a year-old release straight to the latest, and it has to work.

• Keep it boringly simple. A product that ships self-hosted cannot grow a new managed dependency every quarter. You get explicit veto power, and you will need it.

Who you are

You have:

• Shipped software that someone else installs. This is what we screen hardest on. Operating your own cluster is a genuinely different discipline from handing an artifact to a stranger who runs it on infrastructure you will never see.

• Deep Helm expertise — subcharts, conditional templating, values design — plus OCI registries and real exposure to Kubernetes beyond a single distribution: OpenShift and its SCCs, vanilla, RKE2, k0s, whatever you had to survive.

• Worked in air-gapped or heavily restricted environments: image mirroring, offline bundles, egress proxies, custom CA bundles, no external DNS.

• Replaced managed cloud services with self-hosted equivalents — Postgres operators such as CloudNativePG, MinIO or another S3-compatible store, Vault or External Secrets — and lived with the operational consequences.

• Practical software supply chain security: image signing with cosign or equivalent, SBOM generation, distroless or minimal base images, CVE triage.

• Strong infrastructure-as-code and CI (Terraform, Ansible, pipeline matrices). Here the test harness is the product.

• Hands-on experience serving models on GPU — vLLM, NVIDIA NIM or TensorRT-LLM — including VRAM and concurrency sizing and the NVIDIA GPU Operator / Container Toolkit.

• Strong Go and/or Python. You will change application code, not only YAML.

• The judgement and the appetite to say no. Staff here means architectural authority and the willingness to use it.

• Fluent in French and English.

Why join us

• Work on meaningful problems with real-world impact in cybersecurity

• A high-impact role in a small, international, fast-moving team where your contributions directly shape the company and its success

• Shape the future of a product already making noise in AI + security circles

• A company culture that values autonomy and creativity

• Opportunity for equity and early ownership

• We’re flexible on location - you can either work from home or join your colleagues in our beautiful office in Paris’ 9th arrondissement.

If you’re excited about helping security teams adopt cutting-edge AI, we’d love to hear from you. Let’s build the future of cybersecurity together!

Hiring process

1. Intro Call

2. Hiring Manager Interview

3. Technical interview

4. References and Offer