Staff Software Engineer, Search & Retrieval Infrastructure
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At a glance
Job overview
Syllo is hiring a Staff Software Engineer, Search & Retrieval Infrastructure. Syllo seeks a Staff Software Engineer to own and scale its advanced search, indexing, and data scanning infrastructure, optimizing performance and cost as data volumes reach multi‑petabyte scale while ensuring sub‑second latency and high availability.
Key focus areas include Scale the Retrieval Stack: Lead the optimization and architectural evolution of hybrid search infrastructure, Design and implement intelligent cost‑effective tiering across hot, warm, and cold data states, and Drive down latency and cost‑to‑serve by analyzing bottlenecks and tuning indexing algorithms.
Important skills include Software Engineering, Search Optimization, Cloud Infrastructure, Kubernetes, Elasticsearch, and Apache Lucene.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
About Syllo
Syllo is on a mission to transform litigation. Our product is a unified litigation platform that enables lawyers and paralegals to safely harness the power of language models and agentic AI throughout the litigation life cycle. Since going to market, we have gained a diverse group of enterprise customers, including some of the biggest law firms and corporations in the country, and we are quickly expanding. By reducing the expense of litigation industry-wide, we aim to improve access to high-quality representation and promote the alignment of legal outcomes with merit.
About the Role
We are seeking a Staff Software Engineer to take ownership of our advanced search, indexing, and data scanning infrastructure as we scale to the next echelon of data volume.
Our retrieval stack is robust and proven, but as our ingest sizes push into the multi-petabyte range, the complexity of balancing speed, availability, and cost increases exponentially. You will own this constellation of scaling challenges. Your mission is to continuously optimize and evolve our systems—ensuring our hot indexes maintain sub-second latency for interactive workflows, while simultaneously designing highly concurrent, cost-effective architectures for deep scanning and vectorizing massive volumes of cold-storage data. You will lead the design and implementation of sophisticated data tiering and retrieval strategies that keep our platform operating at peak performance without inflating cloud compute costs.
Responsibilities
- Scale the Retrieval Stack: Lead the optimization and architectural evolution of our existing hybrid search infrastructure, maximizing the throughput and efficiency of both lexical search (e.g., Elasticsearch, Lucene) and dense vector databases.
- Advanced Data Tiering & Scanning: Design and implement intelligent, cost-effective tiering strategies across hot, warm, and cold data states. Evolve our distributed pipelines to efficiently execute asynchronous, massive-scale scans of petabytes of data in varying states of availability.
- Relentless Optimization: Drive down latency and cost-to-serve. Deeply analyze system bottlenecks, tune indexing and querying algorithms, and optimize cloud infrastructure (compute, storage, and networking) for maximum efficiency at extreme scale.
- Technical Leadership: Act as the domain expert and owner of the indexing and search ecosystem. Set the long-term technical vision for data storage and retrieval, guiding engineering teams on best practices for high-volume data modeling and performance tuning.
- Resiliency at Scale: Ensure fault-tolerant, highly available operations during massive parallel ingest events and complex, concurrent querying across millions of documents.
Qualifications
- Extreme Scale Experience: 8+ years of software engineering experience, with a proven track record operating at the Staff/Principal level optimizing and scaling highly distributed, high-throughput systems to handle petabyte-level data.
- Search & Vector Mastery: Deep, production-level expertise tuning and scaling Lucene-based search engines (Elasticsearch, Solr) and modern vector indexing infrastructure. You deeply understand index internals, chunking strategies, and embedding retrieval optimization.
- Cost-Aware Architecture: A strong history of managing the compute vs. storage trade-off. You know how to design sophisticated cold-storage scanning solutions and hot-index architectures that are highly performant but fundamentally cost-effective.
- Distributed Systems: Extensive experience managing complex data pipelines, high-throughput event streaming (Kafka, Kinesis), and distributed compute architectures handling billions of records.
- Cloud Infrastructure: Expert command of cloud primitives (GCP preferred), Kubernetes, and infrastructure-as-code.
- Languages: Expert-level proficiency in systems-level and backend languages (Go, Rust, Python, or Java/C++). Salary Range ($190- $230K) plus health insurance and equity.
United States - Remote Pay Range $190,000 — $230,000 USD
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