Platform Engineer
We're looking for a (Senior) Platform Engineer to own and evolve our infrastructure — with a focus on developer experience and the chance to get hands-on with AI systems.
What you'll do
Design and maintain cloud infrastructure on AWS using Terraform
Own and improve CI/CD pipelines for fast, safe deployments
Manage and scale Kubernetes clusters
Improve developer experience — making it easy for teams to ship and debug
Implement monitoring, logging and alerting for full observability
Configure and optimise CDN infrastructure
You are
8-10 years of experience in DevOps, SRE or platform engineering roles
Expertise in AWS
Proficient with Terraform and infrastructure-as-code workflows
Experienced in building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins or similar)
Solid understanding of Kubernetes — deployment, networking, scaling and troubleshooting
Strong sysadmin fundamentals — Linux, networking, storage and configuration management
Comfortable working with relational databases (PostgreSQL, MySQL) and time series databases (TimescaleDB, Prometheus)
A clear communicator who works well across engineering and data science teams
Pragmatic and reliable — you know when to move fast and when to be careful
Nice to have
Experience supporting ML infrastructure — model deployment, GPU workloads or training pipelines
Background in CDN configuration (CloudFront, Fastly, Cloudflare)
Familiarity with streaming data or video processing systems
Interest in MLOps and bridging the gap between ML research and production
Why this role matters
You'll keep our systems running smoothly and help the team ship with confidence. And if you're curious about ML, you'll get real exposure to production AI systems.
#LI-SP1 #LI-Hybrid
What we offer
Employee Share Options Program for all permanent employees*
An increasing benefits list: currently includes Urban Sports club and quarterly team retreats.
Be on the forefront in defining what artificial intelligence means in manufacturing
Gain hands-on experience in working in an AI-first software company
Supportive and inclusive culture that values diversity and promotes the advancement of underrepresented groups within the company
Collaborate with a diverse (currently more than 10 nationalities) and talented team, working on cutting-edge projects with real-world impact
Network with professionals and leaders in the field, opening doors to potential future career opportunities
We have a very flat hierarchy, open 360° feedback, and flexible working hours
Ethics⚖: We are committed to developing ethical AI software
Don't meet all the requirements?
Deltia is committed to creating a workplace that is diverse, fair, and inclusive. We encourage candidates from all backgrounds, even if they do not meet every qualification, to submit their application. We firmly believe that having a team with diverse perspectives only strengthens our company and drives innovation. Our commitment also extends to providing an accessible environment for everyone, including those with disabilities. Please let us know if you require any accommodations during the application process or while working with us, and we will do our best to support you.
*Only full-time, permanent roles are eligible for stock options. Part-time roles, contract roles, work-student, internships and freelance roles are not eligible for stock options.
Skills Required
- 4-6 years of experience in DevOps, SRE or platform engineering roles
- Expertise in AWS
- Proficient with Terraform and infrastructure-as-code workflows
- Experienced in building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins or similar)
- Solid understanding of Kubernetes — deployment, networking, scaling and troubleshooting
- Strong sysadmin fundamentals — Linux, networking, storage and configuration management
- Comfortable working with relational databases (PostgreSQL, MySQL) and time series databases (TimescaleDB, Prometheus)
- Clear communicator who works well across engineering and data science teams
- Pragmatic and reliable — knows when to move fast and when to be careful
- Experience supporting ML infrastructure — model deployment, GPU workloads or training pipelines
- Background in CDN configuration (CloudFront, Fastly, Cloudflare)
- Familiarity with streaming data or video processing systems
- Interest in MLOps and bridging the gap between ML research and production
What We Do
AI-based process analytics platform to increase productivity and quality in manual shop-floor processes. Processes are captured using computer vision and automatically analysed with a highly flexible AI to identify improvement potential. 1. Real-time capture with cameras Cameras are installed at individual assembly stations capturing live video streams of assembly or packaging tasks. 2. AI tracks material & work steps Video streams are continuously analyzed to detect workpiece movements, cycle times, and work step sequencing. 3. Aggregation for data analysis Process data is aggregated per article and production to provide insights on process performance. Video snippets allow for a comprehensive root-cause analysis. 4. Data-driven improvements Your factory managers and process engineers define, implement and measure process improvements to increase productivity and quality in your assembly line.
