Tech Stack
AWSDistributed SystemsGoJavaKafkaMicroservicesPython
About the role
- Design and build scalable microservices that power Proximity’s AI-driven search and discovery stack.
- Develop backend services and APIs to support LLM-powered applications.
- Collaborate with ML engineers and data scientists to integrate RAG pipelines, multimodal models, and inference workloads into production.
- Optimize inference pipelines for latency, throughput, and cost efficiency (e.g., batching, caching, token budgeting).
- Own end-to-end delivery of complex backend projects, from design to deployment and monitoring.
- Write high-quality, maintainable code with rigorous testing and fault-tolerant practices.
- Drive operational excellence through performance tuning, incident response, and root cause analysis.
- Work cross-functionally with Product Managers, Data Scientists, and global engineering teams to translate business needs into scalable technical solutions.
- Deliver robust, resilient backend systems with high availability, reduced inference latency, and lower infrastructure costs.
- Maintain clear documentation and monitoring practices to ensure operational smoothness.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a related field.
- 4–6 years of backend development experience, ideally with exposure to AI or large-scale data systems.
- Proficiency in Java, Golang, or Python with strong coding and system design fundamentals.
- Experience designing and scaling distributed systems at production scale.
- Exposure to LLM inference setups (e.g., vLLM, Hugging Face Inference, Triton).
- Strong debugging, profiling, and performance tuning skills for latency-sensitive applications.
- Knowledge of storage systems, query optimization, and caching strategies.
- Hands-on experience with AWS (preferred), Kafka, and CI/CD pipelines.
- Ability to work autonomously and deliver in fast-paced environments.
- Passion for mentoring engineers and leading by example.
- Curiosity about ad-tech and search systems, and how to optimize them for user and business outcomes.