Senior Backend Developer

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.