Level AI - Staff Software Engineer - Data Pipeline

Job Description

Level AI was founded in 2019 and is a Series C startup headquartered in Mountain View, California.

Level AI revolutionises customer engagement by transforming contact centres into strategic assets.

Our AI-native platform leverages advanced technologies such as Large Language Models to extract deep insights from customer interactions.

By providing actionable intelligence, Level AI empowers organisations to enhance customer experience and drive growth.

Consistently updated with the latest AI innovations, Level AI stands as the most adaptive and forward-thinking solution in the industry.

Position Overview

We seek an experienced Staff Software Engineer to lead the design and development of our data warehouse and analytics platform in addition to helping raise the engineering bar for the entire technology stack at Level AI, including applications, platform, and infrastructure.

They will actively collaborate with team members and the wider Level AI engineering community to develop highly scalable and performant systems.

They will be a technical thought leader who will help drive solving complex problems of today and the future by designing and building simple and elegant technical solutions.

They will coach and mentor junior engineers and drive engineering best practices.

They will actively collaborate with product managers and other stakeholders both inside and outside the team.

What youll get to do at Level AI (and more as we grow together) :

• Design, develop, and evolve data pipelines that ingest and process high-volume data from multiple external and internal sources.
• Build scalable, fault-tolerant architectures for both batch and real-time data workflows using
  
  

• Define and maintain robust data models with a focus on domain-oriented design, supporting both operational and analytical workloads.
• Architect and implement data lake/warehouse solutions using Postgres and Snowflake.
• Lead the design and deployment of workflow orchestration using Apache Airflow for end-to-end pipeline automation.
• Ensure platform reliability with strong monitoring, alerting, and observability for all data services and pipelines.
• Collaborate closely with Other internal product & engineering teams to align data platform capabilities with product and business needs.
• Own and enforce data quality, schema evolution, data contract practices, and governance standards.
• Provide technical leadership, mentor junior engineers, and contribute to cross-functional architectural love to explore more about you if you have :
• 8+ years of experience building large-scale data systems; preferably in high-ingestion, multi-source environments.
• Strong system design, debugging, and performance tuning skills.
• Strong programming skills in Python and Java.
• Deep understanding of SQL (Postgres, MySQL) and data modeling (star/snowflake schema, Hands-on experience with streaming platforms like Kafka and GCP Pub/Sub.
• Expertise with Airflow or similar orchestration frameworks.
• Solid experience with Snowflake, Postgres, and distributed storage design.
• Familiarity with Celery for asynchronous task processing.
• Comfortable working with ElasticSearch for data indexing and querying.
• Exposure to Redash, Metabase, or similar BI/analytics tools.
• Proven experience deploying solutions on cloud platforms like GCP or Attributes :
• Experience with data governance and lineage tools.
• Demonstrated ability to handle scale, reliability, and incident response in data systems.
• Excellent communication and stakeholder management skills.
• Passion for mentoring and growing engineering talent.