Product Engineer

Tenth Revolution Group; Oslo; Hybrid; NOK 990,000 - 1,210,000; Full time

Benefits offered by this job

Equity participation

Job summary

Tenth Revolution Group in Oslo is seeking a Senior AI Product Engineer to own the AI and agent layer from concept to production, combining strong software/product engineering with practical AI integration.

This role emphasizes building production LLM applications, AI agents, and data-driven retrieval with a focus on front- and backend systems and autonomous decision-making.

Qualifications

• Strong backend or full-stack software engineer with autonomous work style.
• Experience with production LLM applications and AI agents.
• Experience with TypeScript/Node.js and cloud deployment.

Responsibilities

• design and build AI agents and tools;
• create integrations between models, internal data and third-party services;
• build MCP-based functionality where appropriate;
• implement retrieval and contextual data access;
• establish AI evaluation and quality measurement;
• develop across the company's TypeScript product stack;
• ship backend and frontend functionality;
• own features from specification through operation;
• make meaningful architectural and product decisions.

Skills

production LLM apps

AI agents

tool/function calling

RAG

retrieval

structured outputs

evaluations

model/API integrations

TypeScript / Node.js

product engineering

cloud deployment

Tools

TypeScript

Next.js

NestJS

MongoDB

LLM APIs

MCP

GCP

Job description

About the company

We're representing a Norwegian technology company that has built a highly differentiated platform around housing and property-market data.

Its proprietary dataset supports products used across the property ecosystem, and the company is now investing in a new generation of AI-driven functionality built directly on top of that information.

The engineering organisation is intentionally small and experienced, with engineers given substantial responsibility over what they build.

The opportunity

We're looking for a Senior AI Product Engineer to own the company's AI and agent layer from concept through production.

This isn't primarily an ML research position.

You’ll combine strong software/product engineering with practical experience building applications using modern LLMs.

What you'll own

You’ll:

• design and build AI agents and tools;
• create integrations between models, internal data and third-party services;
• build MCP-based functionality where appropriate;
• implement retrieval and contextual data access;
• establish AI evaluation and quality measurement;
• develop across the company's TypeScript product stack;
• ship backend and frontend functionality;
• own features from specification through operation;
• make meaningful architectural and product decisions.

What we're looking for

You should be a strong backend or full-stack software engineer who has already moved beyond simply experimenting with LLMs.

Ideally you’ll have experience with several of:

• production LLM applications
• AI agents
• tool/function calling
• RAG
• retrieval
• structured outputs
• evaluations
• model/API integrations
• TypeScript / Node.js
• product engineering
• cloud deployment

You should enjoy operating with considerable autonomy.

Technology

The current environment includes:

• TypeScript
• Next.js
• NestJS
• MongoDB
• LLM APIs / frontier models
• MCP
• GCP
• third-party data and service integrations

Exact framework matching is less important than strong engineering fundamentals.

Useful additional experience

Any exposure to:

• property / real estate
• geospatial systems
• Mapbox
• WMS
• cadastral/property data
• MongoDB
• GCP
• DevOps

would be valuable but isn't essential.

Compensation

Around NOK 1.1M base + stock/options, depending on experience.

Location

Oslo.

Flexible working hours and home-office arrangements.

Norwegian language skills are highly valuable because of customer exposure, although exceptional international candidates can still be considered.

Why join?

You’ll have:

• a highly differentiated proprietary dataset to build on;
• genuine ownership of the AI architecture;
• direct influence over product direction;
• short decision-making paths;
• budget for modern AI tools and frontier models;
• equity participation;
• an experienced, deliberately lean team.

Interview process

1. 20-minute introductory technical conversation
2. Face-to-face discussion centred around something you've personally built, ideally an AI-enabled product
3. References
4. Offer