Senior TechOps Engineer (DevOps / Platform)

Role summary

Senior TechOps Engineer (DevOps / Platform) is a role at QIMA in Lille, Hauts-de-France, France (hybrid). Posted 2026-10-19. Experience level: 5-10.

Job title

Senior TechOps Engineer (DevOps / Platform)

Company

QIMA

Location

Lille, Hauts-de-France, France

Work arrangement

hybrid

Category

DevOps & Infrastructure

Experience level

5-10

Date posted

2026-10-19

Job description

Company Description

“At QIMA, you feel like you belong from Day 1. You join a community of smart minds who not only innovate but also support and inspire each other. Here, we own our work, have fun together, and make every day count.”

QIMA is more than a testing, inspection, certification, and compliance company; we're on a mission to offer our clients smart solutions to make products consumers trust.

With a global reach spanning 120+ countries, we serve the consumer products, food, and life sciences industries, supporting over 30,000 brands, retailers, manufacturers, and food growers.

We combine on-the-ground expertise with digital solutions that bring accuracy and visibility for quality, safety, and compliance data.

What sets us apart is our unique culture: 6,000 Qimates live and make decisions every day by our QIMA Values. With client passion, integrity, and a commitment to making things simple, we disrupted the Testing, Inspection, and Certification industry.

Job Description

Our Vision for Engineering

At QIMA, we expect AI agents to take on a growing share of implementation work: coding, integration, and quality assurance. Engineers remain accountable for review, release, and production outcomes, and focus on what creates lasting business value: deciding which capabilities to build next, defining sound architecture, managing technical debt, and stewarding data and security across the stack. We are investing in the environment, standards, and platforms that make this way of working real.

Your role in the TechOps team

Agents are only as good as the platform they build on and run on. The TechOps team owns that platform: the infrastructure, paved roads, runtime, guardrails, and observability that let engineers and agents ship fast, safely, and with a full audit trail. This is much more than DevOps. As a senior member of high-ownership TechOps team, you will:

Build and own the platform:

Take direct ownership of significant parts of QIMA's core infrastructure and shape it into the engineering platform that delivers our business solutions and operations applications, including our internal AI platform and shared services layer

Architect and evolve CI/CD pipelines and the shared app stack (ingress, monitoring, alerting, backup) using GitOps practices

Design and implement infrastructure as code across our cloud, network, and edge/security layers, balancing short-term delivery with long-term scalability

Enable engineers and agents:

Design self-service paths to production (templates, golden paths, developer tooling) so that product and operations teams can ship business applications quickly, safely, and at scale

Build the AI agent platform: the hosting, context, tool access, guardrails, and evaluation that let agents deliver CI/CD, infrastructure as code, and self-service tasks end to end, with human oversight where it matters

Extend the platform to data and ML/AI workloads (DataOps, MLOps), so pipelines, models, and agents are built, deployed, and monitored to the same standards as application code

Run it reliably and securely:

Join the biweekly on-call rotation, leading incident response and root cause analysis on production issues

Use coding assistants and agentic workflows daily, and embed AI-driven automation into how we deploy, monitor, and operate the platform

Keep the platform secure and auditable by default: secrets, access, logging, and compliance with QIMA quality and security standards, for people and for agents

Shape direction and raise the bar:

Bring outside perspective and industry best practices to the team, and actively challenge existing patterns where they can be improved

Act as a technical reference and informal mentor for other engineers, raising the bar on code quality, operational rigor, automation, and AI adoption

Be directly involved in shaping architecture decisions and technical direction for the team

Qualifications

We're looking for genuine, hands-on seniority - not just years on a CV:

5+ years of experience in DevOps, Platform Engineering, or SRE roles

Proven mastery of using AI to design and build a production-grade AI harness (agents, tools, context, guardrails, evaluation) that carries out tasks end to end.

Strong, production-grade experience with AWS, Terraform, and Kubernetes/EKS

Proven track record architecting and operating CI/CD pipelines (ArgoCD, Argo Workflow, CircleCI, and/or Jenkins)

Experience carrying on-call responsibility for mission-critical systems

Solid expertise with monitoring and observability tools such as Grafana, ELK, and/or OpenSearch

Strong Linux fundamentals and working knowledge of network security

Deep understanding of microservice application architecture in cloud environments

Experience with secrets management (Vault or equivalent) is a plus

Experience building internal platforms or developer tooling (self-service, templates, golden paths) used by other engineering teams is a plus

Comfortable questioning existing practices and proposing better ones, backed by experience

Master’s degree (Bac+5) in Computer Science, Engineering, or a related field, or 5+ years of equivalent professional experience

We’re looking for someone fully engaged with AI - you already use it daily to augment your own work (coding assistants, automation, agentic workflows) and are eager to push it further, building AI into the platform itself and into how the team delivers.

Required: Fluent English , with strong written and verbal communication skills, as you'll work daily with an international team. English is the working language of the team, not a nice-to-have.

Additional Information

What We Offer

Real ownership over company-critical infrastructure, including our internal AI platform, not just execution of existing patterns

An AI-first environment where you are encouraged to push the limits of what AI can do for engineering, with a serious AI