Staff Software Engineer- Databricks AI
Databricks4 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Define the platform strategy and long-term architecture for the MLOps and LLMOps platform.
- Lead engineering efforts from design through production rollout with high standards for performance, correctness, and reliability.
- Solve large-scale problems involving ingestion and querying of traces, metrics, and artifacts and evaluating AI agents in production.
- Align product, research, and engineering teams across sites on technical direction and trade-offs.
- Shape APIs and developer experiences that help customers ship AI systems.
- Mentor senior engineers through design reviews and technical discussions.
- Represent the team externally through blog posts, talks, and open-source contributions to AI frameworks.
Requirements
- Bachelor’s degree or higher in Computer Science or a related field.
- 10+ years of experience developing large-scale distributed systems, scaling infrastructure, or building platforms and developer tools for other teams.
- Strong foundations in algorithms, data structures, and system design.
- Strong backend technical experience with Scala or Java.
- Experience with cloud technologies such as AWS, Azure, GCP, Docker, and Kubernetes.
- Engineering maturity in security, correctness, and operational excellence.
- Proven experience serving as a technical lead, driving architecture decisions, and delivering complex, high-impact projects end to end.
- Ability to lead through influence across teams, communicate effectively, and mentor engineers.
- Experience with ML or LLM systems is preferred.
Benefits
- Databricks offers comprehensive employee benefits and perks, with region-specific details available for the Bengaluru location.
Tech Stack
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.