Description

You will architect, implement, and deploy backend systems and data pipelines to power AI-driven consumer search features.

Responsibilities

• Design, build, and maintain data pipelines for crawling and indexing infrastructure.
• Develop and maintain production SQL and NoSQL databases with performant query patterns for scale.
• Collaborate with machine learning and MLOps teams to ensure infrastructure and data are consumable for user experiences.
• Ship performant, monitored, user-facing production services and debug live production issues.
• Establish architectural patterns, code review standards, and testing practices to help the organization scale.

Required Skills

• 5+ years of professional software engineering experience.
• Experience with distributed processing frameworks such as Databricks, Spark, or stream processing.
• Proficiency with event-driven technologies like Kafka.
• Experience working with REST and Python APIs.
• Hands-on experience with distributed storage and retrieval including SQL, MongoDB, ElasticSearch, and Vector databases.
• Proven track record of deploying mission-critical REST/RPC services.
• Strong focus on testing, including unit and integration tests to cover code paths.
• Experience with Kubernetes (k8s) for managing deployments, configurations, and debugging.
• Ability to build monitoring and observability into production services.

Key Skills

Education

Any Graduate