AI Integration Engineer
No Isolation · Oslo
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- Company
- No Isolation
- Location
- Oslo
- Posted
- August 11, 2026
About this job
About Us At No Isolation, we’re a profitable, 65-person Scandinavian EdTech scale-up operating across Europe. We help educators bring learning and belonging to every child. Our AV1 robot is deployed in 19 countries, with 5,000+ units supporting schools to improve attendance, belonging, and continuity of learning for children who cannot be physically present. Consistently described as life-changing, it bridges the gap between the student and their peers, restoring both educational continuity and the essential sense of social belonging. We’re established enough to have a proven solution and strong financial foundations, yet still small enough for every new colleague to have a visible impact on our next stage of growth. The Opportunity — AI Integration Engineer This is a new role at No Isolation, and you'd be the first person in it. You'll sit inside Engineering but work mostly embedded inside selected internal business units, in contrast to the rest of Engineering. You’ll work with Sales, Customer Success, Finance and Operations. You’ll connect the tools they depend on and implement AI tools and automation flows to positively impact our revenue first and foremost, but also generally enhance internal effectiveness. In practice: you set the bar for how much internal AI and Automation can change the company from the inside in 2026 and beyond, and you co-own the stack you put in place. You will have a lot of direct contact with the teams you're building for, and a lot of say in how the technical side gets structured to enable you, while having the support of experienced software engineers when needed. What You'll Do — Scope & Responsibilities Systems integration: Drive automation of key business areas and connect our business tools across Data, IAM, CRM, ERP (Odoo) and Finance through APIs, webhooks and events, so data stays in sync across systems. Internal automation capability: Build and maintain workflows in Windmill and/or n8n; migrate us off legacy SaaS and iPaaS tools as you go. Aim to articulate as many problems as possible as deterministic automations that keep data and AI cost low. Internal AI capability: Contribute to shared infrastructure for using AI internally alongside our cloud/platform engineers: assistants, retrieval over internal knowledge, summarisation, classification, routing, etc. Turn ad hoc AI experiments into tools people can actually rely on, with eval sets in place to catch regressions. Data & internal foundations: Centralise data into sources the business can trust, reconcile figures across systems so numbers match wherever they appear, and provide internal tools and lightly-built apps. Guardrails & cost control: Define the standards for how integrations and AI get built here. Keep the set of automation platforms small and deliberate (e.g. Windmill, n8n and some custom). Track AI spend and return on investment so we can monitor alignment between the two. Partnership: Work directly with the teams you're building for: understand the actual problem, ship a working increment near-instantly, then iterate and negotiate toward durability. You're measured on time saved, additional revenue generated, budget synergies realised, not on the tools you ship. Share knowledge and lift others through e.g. workshops and townhalls. What You Bring — Experience & Capabilities Talent for working directly with non-technical stakeholders and turning a fuzzy request into a concrete system. This is a first-of-its-kind role here, so you're setting direction rather than following an existing playbook. Experience connecting systems through APIs, webhooks and events: ERPs (Odoo v18 and beyond is a plus), CRMs, or Finance systems. At ease with various application protocols (REST), auth flows (OAuth/SSO) and the rough edges of third-party SaaS APIs. Hands-on with a code-first orchestration platform: Windmill, Temporal, Airflow, n8n or similar. A builder who finishes: Proficient in at least one general-purpose language (Python, TypeScript, Go), and comfortable taking something from rough prototype (built by you or non-technical people) to engineering standard. Comfortable using and configuring self-hosted tooling (containers, secrets, backups, upgrades) to some extent, as opposed to fully leaning on managed SaaS Practical experience with LLMs and agents: context engineering, RAG, evals, tool/function calling. You should have a good sense of where AI helps and where it adds fragility. Data sense: savvy with SQL and common data stores; able to model, reconcile and centralize data; some exposure to classical machine learning can be an advantage. Security-conscious by default: least-privilege access, careful handling of secrets, aware of GDPR, SOC and ISO requirements. STEM degree (BSc/MSc) or equivalent practical experience in integration, AI & automation, or internal tooling. Experience at product or scale-up companies is an advantage. Why You'll Love It Here First-of-its-kind role: you will tackle opportunities unexplo
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