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Antrino Labs is seeking an experienced AI Backend Engineer to build the core intelligence layer of its fast-scaling platform. You will craft backend services, the compiler, and runtime for AI-driven graphs, integrated with LLM APIs and multiple model providers.
You will work across Python and TypeScript services, designing robust APIs and data models. Collaborate with teams in Stockholm and Bangalore to deploy high-quality, auditable pipelines and evolve the platform.
Full-time, permanent, with an initial probationary period of 6 months
As soon as you are available
Antrino Labs is building the platform that makes every square meter intelligent.
The physical world runs on processes nobody can actually see. Goods move, machines idle, space goes unused, and decisions about all of it are based on samples, guesses, and reports written after the fact. Antrino lets any organization deploy vision intelligence into a physical space and get back what is actually happening there, as structured, real-time information it can act on. Not a research project or a custom integration, but a platform where you describe what matters and deploy it.
We have grown from 6 people to a team of 28 in less than a year, closed our Seed round, announced together with Dagens Industri, and are registered with Inspektionen för strategiska produkter (ISP), the Swedish authority for strategic and dual-use products. Everything we build follows Privacy by Design.
You will build the services that turn a customer's intent into working intelligence.
When a customer builds something in Studio, our composition canvas, that graph has to become a running system: a plan that decides which models to call, in what order, gated by cost and confidence, and that produces events and evidence a customer can trust. You will work on the compiler that turns the graph into an execution plan, the runtime that executes it, and the Python and TypeScript services that detection, classification, and measurement run through.
You will also work on our Agent, which interviews customers, proposes and edits these graphs, and deploys them with confirmation. Getting an LLM to reliably manipulate a structured graph, validate it, and explain its reasoning is a real engineering problem, not a prompting exercise.
The role sits between the team building our first-party detection models and the engineers building the product interface. It is backend systems engineering for a product whose core logic is built out of AI calls.
You do not need experience with all of this, but you should recognize most of it and be able to argue about it.
Data: PostgreSQL through Supabase, with row-level security
Streaming: RTSP ingestion, RTSP→HLS conversion, live and archive pipelines
Infrastructure: Azure, GitHub Actions, on-site compute reached over Tailscale
You can reason about a graph or compiler-shaped problem even if you have never built a compiler. You make decisions with incomplete information, take responsibility for the outcome, and say so clearly when something you built was wrong.
You will join a team of driven, ambitious people who thrive at a fast pace and enjoy working together. We go to AI events, host our own, and end plenty of weeks with an afterwork. You will work closely with our engineers in Stockholm and our growing team in Bangalore.
We review applications continuously. References may be requested at the final stage.