Backend Engineer (Mid Level)

About Akerio. Akerio is a UK-based applied AI company. We build platforms that turn messy enterprise data into scored, auditable recommendations: the next diesel price for one of Europe's largest independent fuel distributors, a risk flag on a tenant across 41 shopping centres, a credit score a bank's committee can trace back to the source record. Our models are built by a PhD team from Stanford and the University of Chicago, every output shows what drove it and how confident it is, and the platform runs on-premise or in the cloud. We are live in production across energy, commercial real estate and financial services, with 18 AI modules running in one deployment alone. We are a small team shipping to demanding enterprise clients, so the work you do reaches production and gets used. • Job: Full time • Job type: Remote The role Our retail property analytics platform, live across 41 shopping centres, runs on a set of NestJS microservices: a core business service, an AI service that calls LLM tools, a notification service, and a Python compute service that serves forecasts and risk scores. Every month Airflow retrains and reruns revenue, footfall, tenant risk and mall performance models, and the backend has to get those results to the screen fast and correctly. You join the team that builds and runs these services. You will write production code from your first month, with a senior reviewer on every pull request. What you will work on • NestJS endpoints for leasing, finance, visitor and budget modules: DTOs, validation, permissions, and the SQL behind them. • PostgreSQL and PostGIS: schema changes, migrations, query tuning, statement timeouts on heavy reports. • Service-to-service work over gRPC and Kafka, Redis caching, and real-time updates over Socket.IO. • Endpoints that Airflow calls to run forecasts and write back results and accuracy metrics. • The AI service: tool definitions the LLM can call, MCP integration, caching AI commentary, logging every conversation to Langfuse. • Python FastAPI work in the compute service when a model needs a new input or output. • Production hygiene: health endpoints, log rotation, monitoring alerts, dependency and security upgrades flagged by Trivy. Our stack Area What we use Services Node.js, TypeScript, NestJS, Yarn workspace monorepo, gRPC, Kafka, Redis, OpenSearch, Socket.IO Compute Python, FastAPI, pandas, scikit-learn Data PostgreSQL 17, PostGIS, SQL migrations Scheduling Apache Airflow AI Anthropic Claude via API, tool calling, MCP, Langfuse Infra Azure, Docker and Docker Compose, nginx, pm2, Jenkins, Bitbucket, OpenTelemetry and Jaeger, Trivy How we build Jira, spec-first work with AI coding tools (Claude Code), code review on every PR Your first six months • First month: environment running, first fix merged in week one, then one endpoint shipped with tests. • Month three: you own a module's backend (for example finance or budget) and its test suite. • Month six: you take a feature from spec to production with light review and handle its production issues. What you bring Junior (0 to 2 years): • A computer science or engineering degree, or equivalent proof that you can build software. • TypeScript or JavaScript you have used on something real: an internship, a serious side project, open source. Node.js is a big plus. • SQL beyond SELECT: joins, indexes, transactions. • Git, the command line, and the habit of reading the docs before asking. Mid (2 to 4 years): • Production backend experience in Node.js and TypeScript, ideally NestJS. • You have designed REST APIs and PostgreSQL schemas other people built on, and written migrations that ran on live data. • Testing as a habit: unit and integration tests with Jest or similar. • Docker, CI pipelines, and you have debugged a service in a deployed environment. Both levels: clear written English, curiosity about how the data is used, and comfort with AI coding tools while still owning every line you merge. Turkish is a plus. Nice to have • Python and FastAPI. • Kafka, gRPC, Redis or any event-driven microservice work. • PostGIS or other geospatial data. • Exposure to LLM APIs, tool calling or MCP. • Azure, Linux server administration or monitoring setup. How we work Spec before code, code review on every pull request, and a Jira board fed by real client feedback every week. Juniors pair with a senior every week. Hiring process 4. 30-minute intro call. 5. 30-minute session: present your case to the CPO and an engineer. 6. 15-minute call with a founder. What we offer • Fully remote, with overlap on UK and Türkiye working hours.