Relativity is seeking a Lead Software Engineer to join the Retrieval Ingestion Team to design and operate high throughput ingestion pipelines that transform raw documents into search-ready indexes at scale.
Requirements
- Proven expertise in building distributed ingestion or ETL systems for search or largescale data platforms.
- Deep knowledge of indexing/search systems (Elasticsearch, Lucene, Solr, Vespa, or OpenSearch).
- Strong programming skills in C-Sharp, Java, Python, or Go, with emphasis on reliability and performance.
- Familiarity with schema evolution, metadata modeling, and handling semi/unstructured data for indexing.
- Hands-on experience with Kubernetes, containerization, and CI/CD pipelines in cloud environments (Azure, AWS, or GCP).
- Strong background in observability and operational resilience for ingestion systems.
- Experience integrating embeddings and vector databases into ingestion workflows.
Responsibilities
- Lead the Retrieval Ingestion Team, providing technical direction, mentoring, and coordination across projects.
- Architect and maintain scalable ingestion pipelines that handle billions of documents reliably and efficiently.
- Drive adoption of event-driven and micro-batch ingestion frameworks using Kafka, Kinesis, or Flink.
- Collaborate with retrieval engineers to ensure ingested data is optimized for indexing and retrieval performance (sharding, metadata enrichment, incremental updates).
- Establish SLAs and monitoring for ingestion throughput, latency, data completeness, and recovery.
- Partner with platform, security, and compliance teams to ensure ingestion pipelines handle sensitive legal data securely and meet enterprise standards.
- Champion best practices in CI/CD, observability, automated testing, and operational readiness for ingestion systems.
Other
- 6+ years of professional software engineering experience, including 2+ years in a lead role.
- Mentor engineers and shape best practices for ingestion and indexing across the organization.
- Join a cloud-native engineering culture investing in scalable, AI-enabled retrieval systems that transform how legal data is discovered.
- Competitive base salary, an annual performance bonus, and long-term incentives.
- Total compensation which includes a competitive base salary
