Salary :
Activate JobCopilot
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.
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