Back End Engineer

Key Responsibilities

1. Design, build, and maintain the backend systems and APIs for our ad marketplace, campaign management, and analytics/attribution pipelines.
2. Contribute to the data platforms and ad-serving systems that process and act on data at scale.
3. Help build and maintain the backend infrastructure for our autonomous AI agents.
4. Work with product, other backend engineers, and DevOps to ship end-to-end features.
5. Model and manage data in SQL (MySQL, PostgreSQL) and NoSQL (MongoDB, Redis) databases, including caching where useful.
6. Implement authentication, authorization, and data security practices with guidance from senior engineers.
7. Write clean, well-documented, well-tested code.
8. Deploy, monitor, and scale services on cloud platforms (AWS, GCP, or Azure).
9. Containerize backend services with Docker (Kubernetes optional).
10. Contribute to and help maintain CI/CD pipelines.
11. Monitor and debug production issues using observability tools such as Prometheus, Grafana, or ELK.
12. Take part in code reviews and help shape team development standards.
13. Work within event-driven and microservices architectures, using GraphQL, WebSockets, or message brokers (Kafka, RabbitMQ) where they fit the problem.

Requirements

1. 2-4 years of professional backend engineering experience.
2. Proficiency in at least one backend language (e.g., Python, Java, Node.js, Go, or Ruby).
3. Strong understanding of RESTful API design and asynchronous programming.
4. Solid experience with relational and NoSQL databases, including basic data modeling.
5. Familiarity with Docker, Git, and modern CI/CD workflows.
6. Hands-on experience deploying to cloud infrastructure (AWS, GCP, or Azure).
7. Working knowledge of backend security best practices.
8. Strong problem-solving, debugging, and communication skills.
9. Comfortable in a fast-paced, agile environment with changing priorities.

Good to Have

1. Exposure to monitoring, logging, or performance profiling in production.
2. Experience with message brokers (Kafka, RabbitMQ) or GraphQL.
3. Experience with Kubernetes.