Backend Developer, Product and Data

Someone researching a purchase might start in ChatGPT, compare options in Perplexity, run a Google search, then go back to an AI assistant to decide. The companies being compared have little idea where they show up in that chain or what gets said about them, and very few can measure it today.

We build the infrastructure that measures it. Every platform we track changes under us, and none of them offers a feed, so we collect the data ourselves. Three products run on it:

• AccuRanker is the rank tracking and SEO analytics platform. Rankings, competitor movement, keyword research, dashboards, forecasting.
• AccuLLM tracks brand visibility inside ChatGPT, Perplexity, AI Overview, and AI Mode.
• AccuSERP is a search data API we sell to other companies in the industry.

On a normal day that means 27 billion rows inserted, 85 million web requests collected, 80 million background jobs run, and 64 million analytical queries served. Eight people build and run all of it.

This job is on the product side: the backend, the data models, and the query paths that run on top of what we collect.

What you will work on

• Build features across AccuRanker and AccuLLM: Django APIs, background jobs, and the data models behind them.
• Write and tune queries against Postgres and ClickHouse, and help keep the 64 million daily analytical queries fast as the data grows.
• Start with scoped changes to existing services, and grow into owning services yourself, from design through deployment to how they behave in production.
• Take features into the React frontend if you want to. Fullstack is welcome, not required.

What you bring

Must have :

• Solid programming fundamentals. You write clear code and can reason about what it costs at runtime.
• Code of yours running somewhere real. A production system at work, a service you host yourself, or a side project with actual users.
• A web framework and a relational database. You have built something real with Django, Rails, Express, or similar, and you can write and read SQL.
• Ownership. You take a problem, decide how to attack it, ask when you are stuck, and follow through.

Good to have:

• Python and its common frameworks (Django, Celery, pandas/polars). Our stack runs mostly on Python, but it is not a must if the fundamentals are strong.
• React and TypeScript, for the optional frontend part of the job.
• ClickHouse or another columnar store.
• Comfort in Linux. Reading logs, following a request through a system, finding out why something is slow.
• Kafka.
• AI agents. Tool and context design, structured output and evals.

All of it can be learned here.

Who does well here

People who set a high standard for their own work, and who care about performance, reliability, cost, and operational simplicity.

You want to own a feature end to end, from idea to production. The problems we hand you will be scoped at first, and less so over time, and a month after something ships, you are still the one who cares about it.

You move fast when speed is what the problem needs, and you know when stability, safety and maintainability matter more.

This field moves fast right now. We expect you to read, try things, and form your own view of what is worth using, without waiting to be told what is new.

The job is wide. In one week you might tune a query, ship a customer-facing feature, and design an agent.

This role is not for you if you want a narrow technical scope or a large team around you. We are small, the problems change, and you will get real responsibility earlier than most places give it. The senior engineers sit next to you, and asking them is part of the job.

AI at AccuRanker

AI is a big part of the product and of how we build it. AccuLLM sends queries to LLMs all day, customers use our MCP server, and agents and tool design are real engineering problems here.

Being effective with coding agents is becoming a core engineering skill, and it is part of this job. You should be good at giving agents the right context, breaking work into pieces they can execute well, reviewing what they produce, and knowing when to take over yourself. The bar is more high-quality engineering done without outsourcing your understanding and judgment, which is a different thing from using AI a lot.

How we work

• You own services, not tickets. You decide how to solve the problem, make the tradeoffs, and deploy it yourself.
• We ship many times a day. A change can go from idea to production the same day.
• We argue about designs, in writing and in the room. Correctness, cost, and latency are worth arguing about out loud.
• We share what we know and help each other own unfamiliar parts of the system.

What we offer

• Salary set individually on skills and experience.
• Pension, health insurance, flexible working hours, and paid parental leave.
• Hardware of your choosing.
• Office in central Aarhus on Åboulevarden, top floors, panoramic views over the city. The role is on-site, with hybrid options planned for later this year.
• Great lunch.