Senior Backend Developer

2 weeks ago

San Francisco, United States Weekday Full time

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Mid-Senior level Salary range: $180k - $250k Experience: 6+ YoE $180,000 - $250,000 a year We’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 Do Build 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 For Experience: 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 Have Hands‑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 Role Work 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. #J-18808-Ljbffr

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