AI Platform Engineer

Swiatowid — Poland · Posted ~2 hours ago

Full-time

Skills

AI engineering Backend engineering Data pipelines Event-driven systems API integration Databases Search systems Distributed systems AI Backend APIs Search Multi-agent systems

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Summary ✨ AI‑Generated

Join a team building an intelligence and forecasting platform that combines AI with large-scale information and data signals. You will design platform architecture, build production AI workflows, develop event-driven data pipelines, integrate models with external systems, and work on retrieval, verification, forecasting, and multi-agent reasoning.

Highlights

Build production AI workflows and evolve architecture across AI, backend, data, and forecasting systems. The role provides broad ownership over data pipelines, real-time processing, integrations, and advanced AI capabilities.

Description

Swiatowid is an intelligence and forecasting platform designed to turn complex, fast-moving information into clear, actionable insight. It combines human and AI forecasts with public sources, market data, blockchain activity and other signals to estimate future events, explain the factors behind those estimates and continuously update them as new information arrives. We are building a platform for business, financial, geopolitical and security use cases where the quality, provenance and confidence of information matter. What you'll do • Design and evolve the platform architecture across AI, backend, data and forecasting systems. • Build production AI workflows for research, retrieval, source analysis, verification, forecasting and multi-agent reasoning. • Build reliable data pipelines and event-driven systems for continuous ingestion, processing and forecast updates. • Integrate AI models with APIs, databases, search systems, external services and real-time data sources. • Build systems for source quality, provenance, deduplication and signal independence. • Design evaluation and testing systems for AI workflows, including accuracy, calibration, reproducibility and regression testing. • Build and operate cloud infrastructure using Docker, Kubernetes, CI/CD and infrastructure as code. • Own production reliability, scalability, observability, latency and infrastructure cost. • Make pragmatic decisions about where AI adds value and where deterministic software is the better solution. • Work closely with product and business to turn requirements into reliable, scalable systems. What we're looking for • 3–5 years of experience building and operating production systems in backend engineering, applied AI, ML infrastructure or distributed systems. • Strong Python and TypeScript skills. • Hands-on experience with LLM applications, tool calling, structured outputs, RAG or agent-based systems. • Strong understanding of APIs, databases, asynchronous processing, queues and distributed systems. • Production experience with cloud infrastructure, with AWS as the primary environment. • Hands-on experience with Docker, Kubernetes, CI/CD and infrastructure as code. • Strong understanding of observability, monitoring, tracing, logging and production debugging. • Experience designing testing and evaluation for AI systems where correctness cannot be measured through traditional unit tests alone. • Strong architectural judgement and the ability to make and own technical decisions in production. • Strong product sense and the ability to balance reliability, performance, cost and development speed. • Native or near-native Polish. • Professional working proficiency in English. Nice to have • Experience with Azure and its cloud services. • Experience with forecasting, prediction markets, financial data, blockchain, OSINT or intelligence systems. • Experience with real-time data pipelines, search, knowledge graphs or event-driven architectures. • Experience building and evaluating multi-agent AI systems in production. • Experience operating AWS infrastructure at scale.