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Scandit

Senior Backend Engineer - Shelfview

Scandit is hiring a Senior Backend Engineer - Shelfview in Tampere, Finland. Level rates it ; you can apply on Scandit.

Level's read on this job

  • On Level's scale, this software engineer role is Little AI ●○○○: aI is not part of the work.
  • The posting mentions Claude, Vertex AI and Claude Code among its tools and skills.
  • Level classes it as a senior role.
  • Scandit has 11 other open roles on Level.

AI in this role

claudevertex-aiclaude-code

Scandit Tampere

Senior Backend Engineer

Imagine the What. Build the How.

Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication or allowing retailers to make store operations more efficient, our technology automates workflows and provides actionable insights to help businesses in a variety of industries. Join us, as we continue to expand, grow and innovate, and help take Scandit to the next level.

Our newest product, ShelfView, is a machine-learning-powered platform for retail that gives real-time shelf visibility and helps stores run more efficiently. ShelfView is scaling fast: we are ramping towards the rollout of the largest retail intelligent deployments, processing billions of product-location updates a year. As a Senior Backend Engineer, you’ll be part of the team that builds and runs the backend behind ShelfView's product recognition and store-monitoring pipeline.You will help scale automated, ML-driven store monitoring while keeping the platform fast, observable, and secure for a growing list of enterprise retail customers.

If these challenges sound interesting to you, we'd love to hear from you!

About the Role

This role is about solving complex engineering problems at scale and building the backend solutions that power them. You will help design and operate the distributed systems that turn store imagery into real-time, actionable alerts. That includes choosing and building on workflow-orchestration infrastructure for ML pipelines, making infrastructure and GPU-capacity tradeoffs for model serving at scale, and extending our identity and multi-tenancy platform as we bring on larger, more security-conscious customers. You will also help the team see what is happening in production through better observability, and mentor other engineers along the way.

What You Will Do

  • Bring the platform to the next level: load- and stress-test it against our largest deployments yet, and close the gaps that surface
  • Push our infrastructure and GPU capacity strategy further to support larger, more demanding deployments
  • Collaborate closely with AI/ML researchers/engineers to put their innovations to production
  • Extend and harden our multi-tenancy platform for new customers and regions
  • Deepen observability so the team can find and fix production issues even faster
  • Design and evolve our service APIs as the platform grows
  • Mentor other engineers and help set technical direction as the team scales

Our Tech Stack

  • Python / Django
  • Postgres
  • Temporal (workflow orchestration)
  • PubSub
  • GCP / AWS, including GCP Identity Platform and Vertex AI for model serving
  • OpenTelemetry, Grafana Tempo / Jaeger
  • GitLab

Who You Are

We are looking for an experienced backend engineer who is comfortable owning a problem end to end: evaluating a handful of possible technical approaches, shipping the one you picked, and operating it under real production load. You care about making systems observable and debuggable, not just functional. You have made infrastructure tradeoffs before, deciding what hardware, architecture, or vendor to use, and why, and you can back that decision with data. You enjoy mentoring other engineers and raising the technical bar for the team.

  • 5+ years of professional experience as a backend engineer shipping software in the cloud
  • Have evaluated and adopted workflow-orchestration or distributed-pipeline tooling (e.g. Temporal, Celery, Airflow, Dagster, or similar) for a production system
  • Have hands-on experience with identity/auth systems (SSO, OAuth/OIDC, RBAC) and multi-tenant architectures
  • Are comfortable with observability tooling (distributed tracing, metrics, structured logging) and have used it to debug production issues
  • Are fluent in multiple languages, Python being your strongest
  • Have first-hand experience with databases (relational and document-oriented), service-oriented architectures, cloud data pipelines (stream and batch), Docker, Kubernetes
  • Are familiar with automation testing, continuous integration, continuous delivery, and are comfortable using AI coding tools as part of your day-to-day workflow
  • Have broad, T-shaped experience: comfortable across infrastructure, backend, data, and frontend, with real depth in at least one of those areas
  • Are experienced with Infrastructure as Code (e.g. Terraform) for provisioning and scaling cloud infrastructure
  • Have operated production systems at scale and bring established best practices from similar systems (workflow orchestration, multi-tenant SaaS, real-time ML pipelines)
  • Are willing to go beyond your role, your team, and (sometimes) your comfort zone to make a cross-functional impact on the business
  • Are eligible to work in the hiring location

Nice to Have:

  • Experience serving machine learning models at scale (GPU capacity planning, model-serving infra, cost optimization) in an industry setting

Our Approach To AI

AI is part of how we work. Scandit embraces AI-native engineering, where engineers direct agents to deliver customer outcomes, using the tools they choose. We want to know how you use them, where you’ve hit their limits, and how you keep improving human-agent collaboration. We take pride in our craft, and that means making sure what agents deliver meets our quality bar.

What We Offer

Here are some of the reasons people choose to build their career at Scandit:

  • Certified as a Great Place To Work for four years in a row
  • Rated 4/5 by our employees on Glassdoor
  • Access to Claude Cowork and Claude Code, plus a budget to experiment with other AI tools
  • Weekly “How to Use AI” sessions and internal AI Champions to help turn your ideas into reality
  • A share in our success through an individual equity plan
  • Extra days off on top of your annual leave
  • Office shutdown days, global team events and innovation hackathons

Plus specific benefits depending on the location you are joining.

You could be the difference

At Scandit we strive to create an inclusive environment that empowers our employees. We believe that our products and services benefit from our diverse backgrounds and experiences and are proud to be a safe space for all.

All qualified applications will receive consideration for employment without regard to race, colour, nationality, religion, sexual orientation, gender, gender identity, age, physical [dis]ability or length of time spent unemployed.

Imagine the What. Build the How.

#LI-MB1

#LI-Hybrid

#engineering

#LI-midsenior

How we rate this

Senior Backend Engineer - Shelfview at Scandit rates 6 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ClaudeVertex AIClaude Code

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$168k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. What's a project where you used Claude hands-on?
  2. Walk me through how you've used Vertex AI in your day-to-day work.
  3. What are the limits of Claude Code that you've run into, and how did you work around them?

Adapt your resume

  • List these exact terms on your resume: Claude, Vertex AI, and Claude Code. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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