Qureos

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Backend Engineer

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Responsibilities

  • Architect and build core backend infrastructure using Python and FastAPI

  • Design and optimize PostgreSQL databases for production workloads at scale

  • Build complex workflow orchestration systems for agentic services and automation

  • Implement caching strategies with Redis for high-performance data access

  • Build monitoring, logging, and alerting systems with tools like Prometheus and Grafana

  • Create and maintain CI/CD pipelines for rapid, reliable deployments

  • Containerize services with Docker and orchestrate with Kubernetes

  • Work independently with minimal direction in an ambiguous, fast-paced environment

  • Establish engineering standards, security practices, and technical culture

  • Own systems end-to-end from design through deployment, scaling, and incident response

Requirements

  • 7+ years building production backend systems from concept to scaled deployment

  • Expert-level Python with significant FastAPI experience in production

  • Deep PostgreSQL proficiency: complex queries, optimization, schema design, performance tuning

  • Production experience with Redis for caching, session management, and real-time data

  • Hands-on experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)

  • Proven track record implementing CI/CD pipelines and deployment automation

  • Experience with monitoring/observability tools and maintaining system reliability

  • Thrives with autonomy, minimal direction, and ambiguous early-stage problems

  • Strong system design, security, and operational excellence instincts

Nice to Have

  • Backend infrastructure for AI/ML applications or agentic systems

  • Experience building workflow products or workflow orchestration platforms

  • Managing headless browsers (Playwright, Puppeteer) at scale in production

  • Experience with Neo4j or other graph databases for complex relationship modeling

  • Track record scaling systems from hundreds to millions of requests

  • Previous startup experience shipping rapidly and iterating based on feedback

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