Responsibilities
- Build AI-powered customer experiences — integrate LLMs and advanced causal inference techniques into production workflows that automatically generate data visualizations, synthesize campaign performance into natural language insights, and help enterprise customers understand and optimize their advertising through our AI analyst "Bayes."
- Design and build scalable backend systems — develop microservices and RESTful APIs that power the analytics platform behind the world’s top brand campaigns.
- Contribute across the stack — work from backend APIs to Python analytics services to React frontends, delivering complete features that combine sophisticated data analysis with intuitive user experiences.
- Engineer data pipelines at scale — design and operate systems that process massive volumes of ad and survey data with MySQL, DynamoDB, and AWS (S3, Lambda, EMR, Kinesis Firehose).
- Improve reliability and performance — deploy services on Kubernetes and AWS, automate deployments via CI/CD, monitor with DataDog and Sentry, and continuously raise the bar for operational excellence
- Collaborate deeply — work closely with Product and Data Science to productionize statistical models, integrate advanced analytics into customer-facing tools, and bring cutting-edge AI capabilities to enterprise customers.
- Deliver insights that move millions — enable brand lift analytics and real-time campaign insights by building reliable, high-throughput systems. Multi-million dollar advertising decisions hinge on our recommendations.
Compensation
The annual base salary range for this role is $150,000 - $175,000 + bonus + equity + benefits.. Equity: true
Team
Structure: humble but ambitious team
