Lead Engineer- Java FS with Streaming

Overview

We are looking for a skilled and motivated Lead Engineer to join the Cosmos.AI platform team, focusing on development of data driven AIML. You will design and build highly performant backend systems to serve features at low latency, includes feature store, streaming, vector search and graph compute platforms, ensure consistency between training and inference environments, and integrate with a set of data storage and computation layers. This is a high-impact role on a technically ambitious team, working at the intersection of AI, big data, and platform engineering.

Responsibilities

• Design, build, and maintain robust, scalable backend services for AI / ML Feature platform using Java, Spring Boot, and modern cloud-native technologies.
• Develop APIs and runtime systems to support low-latency, multi-modal feature serving (aggregation, structured, vector, time-series, graph-based, etc.).
• Implement AI / ML computation applications, both real-time and batch, integrating with streaming platforms (e.g., Kafka, Dataproc) and storage.
• Ensure data / feature consistency and parity between online and offline environments to avoid training / serving skew.
• Optimize system performance through caching strategies, asynchronous processing, and storage selection tailored to feature types.
• Build and maintain integration layers with upstream data producers and downstream model inference consumers.
• Implement monitoring, alerting, and observability features to ensure production reliability.
• Collaborate cross-functionally with Data Science, MLOps, Infrastructure, and Governance teams to deliver end-to-end capabilities.
• Participate in on-call support rotations and contribute to incident resolution and root cause analysis.

Requirements

Why Join Us

Skills Required

Java, BigQuery, Prometheus, Kafka, Spring Boot, Dataproc, Hbase, Docker, Neo4j, Influxdb, Spark, Kubernetes