Senior Backend Developer at Weekday

This role is for one of our clientsIndustry: Technology, Information and MediaSeniority level: Mid-Senior levelSalary range: $180k - $250kExperience: 6+ YoE$180,000 - $250,000 a yearWe’re building the next generation of AI-powered platforms that turn complex data into real-time, actionable insights. As our Senior Backend Engineer, you’ll be at the heart of this mission—designing, developing, and scaling the systems that fuel AI-driven products, high-performance data pipelines, and intelligent automation.If you love working at the intersection of AI, backend architecture, and large-scale data engineering, this role will put you in the driver’s seat of innovation.What You’ll DoBuild AI-First Backend Systems: Architect and maintain backend services that integrate and serve AI/ML models at scale with low-latency performance.Design Powerful APIs: Create secure, high-performance APIs that deliver AI insights seamlessly to products, platforms, and external partners.Own ETL Pipelines: Develop and optimize ETL workflows for ingesting, transforming, and delivering structured and unstructured data from diverse sources.Scale for the Future: Ensure systems are resilient, observable, and performant—even under massive load.Collaborate Across Disciplines: Work closely with data scientists, frontend engineers, and product teams to bring AI-driven features from concept to production.Champion Best Practices: Lead efforts in performance tuning, security hardening, and code quality to ensure a robust engineering foundation.What We’re Looking ForExperience: 6–10 years in backend engineering or related roles, ideally in AI/data-heavy environments.Tech Mastery: Strong proficiency in Python and TypeScript (Node.js) for backend services.ETL Expertise: Proven track record in building, scaling, and maintaining complex ETL pipelines for high-volume data.Data Handling: Skilled in working with both relational (PostgreSQL) and non-relational (MongoDB) databases.Cloud & Containers: Comfortable deploying to AWS, GCP, or Azure with Docker/Kubernetes.Systems Thinking: Strong grasp of distributed systems, asynchronous processing, and performance optimization.AI Integration: Experience deploying and scaling AI/ML models into production systems.Nice to HaveHands-on experience with data orchestration tools (Airflow, Prefect, Dagster).Familiarity with real-time streaming platforms (Kafka, Kinesis).Exposure to MLOps frameworks (MLflow, Kubeflow, Vertex AI).Knowledge of data governance and compliance in AI-driven systems.Why You’ll Love This RoleWork on bleeding-edge AI applications with direct product impact.Own critical systems from design to deployment.Collaborate with a small, high-talent team that moves fast and ships often.Shape the technical foundation of a rapidly growing platform.