Teach AI to understand a company's revenue data, so marketers stop waiting for engineers.

At N.Rich, agents write most of the code. Engineers lead the agents and own the judgement: what to build, what not to build, and whether the answer is correct.

About N.Rich

N.Rich is the buildable ABM platform for B2B revenue teams. We find the accounts showing buying intent, put ads in front of them through our own DSP, and show sales when to move. More than 250 go-to-market teams use N.Rich, including GE HealthCare, JetBrains and Wärtsilä. We were founded in Helsinki in 2015.

Our newest product, N.Rich AI, is now the centre of the company. Teams describe what they need in plain language, and N.Rich AI builds a live app on their own data and acts on it.

One set of numbers: a governed data layer joins CRM, website, LinkedIn and ad data, so every app gives the same answer.
Proof of impact: it shows which programmes and channels created pipeline, reconciled to the customer's own reports.
Action: accounts an app finds become ad audiences or Salesforce and HubSpot lists, and results flow back in.

Why now

N.Rich AI solves the problem others avoid. Competitors use AI for small things, like more ad variations. N.Rich AI shows what marketing did for revenue, on numbers finance trusts.
The next few quarters decide the category. A lead like ours does not last forever. What you ship in your first months goes straight to customers.
We are opening the product up. Anyone can now try N.Rich AI without a sales call. Builders who share apps on it can join our partner programme. Every shared app brings in the next user.
We ship fast. The N.Rich AI playground went from idea on 17 September to a beta in production a month later. On 10 September the team said AI apps couldn't move between our EU and US regions. One week later, one-click transfer was live, with design and review.

Problems you will work on

A semantic layer on clients' CRM data. Build it on top of clients' Salesforce and HubSpot data, so AI understands their business and can answer real questions about it.
Our own AI harness for revenue teams. Marketers and sales people do things on their own that needed engineers before.
Who is behind a website visit. Identify the people behind website visits with our own algorithms, on top of the data we already have.

How we work

Everyone at N.Rich works through their own AI system, not just engineers. We pay for models and tools from more than one provider, so you can experiment freely and use what fits each task best. Our team works from 20+ countries. You join an R&D team of 17 people (8 developers, 3 data scientists, QA, DevOps and design) and report to Anton, our CTO. You work closely with product and revenue.

You will fit if you

Have shipped projects that run in production with real users and real problems, and owned them from the goal to production.
Work every day through your own AI setup: agents connected to your tools, a model from another provider reviewing their work, repeated work turned into skills. For Tech lead, agents also keep working in the background. You will show it to us live.
Make technical decisions that still hold a year later, including "let's not build this".
Spot problems early, in or outside your area, and bring a fix.
Care who the work is for, and talk to product and revenue to find out.

You probably already have: 5+ years as a software engineer, strong experience in one popular language (TypeScript, Java or Python), SQL and relational databases, APIs, distributed systems basics, Docker and CI/CD, fluent English.

A bonus, not a must: agents, MCP servers or skills others use; LLM-based products; data and analytics platforms; marketing or ad tech; Salesforce or HubSpot integrations; event-driven systems.

This is not for you if you

Can't make decisions on your own.
Need a fixed roadmap and stable priorities.
Aren't ready to change fast.
Don't want to talk to clients.

What we expect from each other

Four values guide how we work. We call them C.O.R.E., and we hire, give feedback and grow against them.

Context & System Thinking. Know why the work matters before you start. Understand who it's for and what else it touches.
Ownership. Own the outcome, not the task. Raise risks early and take responsibility for the result, not the handoff.
Radical Candor. Challenge ideas directly and assume good intent. We keep problems small by talking about them early.
Execution at Scale. Ship fast, check the results, and turn what works into systems that run and improve without us.

From the team

"Join us to be on the frontier of the AI change instead of watching it from the sidelines. At N.Rich we expect everyone to become an engineer, and R&D is at the center of it." (Anton, CTO)
"What's different here is that we leverage AI at every step of building N.Rich AI, and engineers are responsible for the outcome. You decide how to solve the problem and take a feature all the way to production, with people who challenge ideas openly and care about the result." (Oleksiy, Senior Software Engineer)

Pay and terms

Per month. This is a contractor role. We place you in the range based on what you show us when we get to know each other.

Senior: up to €7,500 per month
Tech lead: up to €10,000 per month

You can work from anywhere within about 2 hours of CET. We can't contract in every country, so we confirm your location in the first talk. We pay for the tools you need to do the work, including AI models from more than one provider, so you pick what works best.

How we get to know each other

No take-home tasks. Apply with your CV or your LinkedIn profile.

Intro call. A short call with our HR Director to get to know each other.
Values conversation. How you work, talked through against our C.O.R.E. values.
Technical prescreen. 30 minutes with Anton, our CTO.
Technical interview. 2 hours. A technical task from our domain, worked through live on the call.
Final talk with Anton. Only if we need it after the earlier steps.

In the application we ask one question: describe your AI setup. What does it connect to, who reviews the agents' work and how, and what are your main learnings?

Senior Software Engineer (Backend, AI)

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