Principal Search Engineer - Java, Elastic Search, Solr
Owns the architecture and operation of Nasuni’s multi-tenant distributed search and MCP platform, spanning ingestion, indexing, query execution, relevance, and reliability. Requires 10+ years of software engineering experience, deep Java expertise, and substantial production experience with large-scale search systems.
About the job
Responsibilities
- Architect and own the end-to-end search and MCP platform, including ingestion, indexing, query execution, and relevance tuning.
- Define and evolve scalable OpenSearch-based architectures for multi-tenant SaaS environments.
- Lead performance optimization efforts to meet strict SLOs for latency, throughput, and availability.
- Establish best practices for cluster management, observability, and incident response.
- Partner with Product and Engineering leadership on multi-year technical roadmaps.
- Serve as the primary technical integration point between search and core product teams.
- Mentor and guide engineers through technical reviews and architectural decision-making.
Requirements
- 10+ years of overall software engineering experience, with 7+ years focused on search systems.
- Hands-on production experience with OpenSearch, Elasticsearch, or Solr.
- Proven ownership of large-scale, multi-tenant search platforms with terabytes of indexed data or more.
- Deep expertise in Java, including high-performance, low-latency services.
- Strong understanding of distributed systems, fault tolerance, and data consistency.
- Experience operating search systems in cloud environments, including AWS and/or Azure.
- Production experience with Kubernetes-based deployments.
Nice-to-haves
- Advanced relevance tuning experience, including custom analyzers, tokenization, and scoring models.
- Experience designing search ingestion pipelines for unstructured data.
- Operational ownership of on-call, incident response, and reliability metrics.
- Working knowledge of Python for scripting, tooling, or data pipelines.
- Experience with Learning to Rank or machine-learning-based relevance models.
- Prior ownership of a search platform serving hundreds of customers.
- Experience modernizing or replacing legacy search architectures.
- Contributions to OpenSearch or Elasticsearch ecosystems, or to internal platform frameworks.
Compensation and Benefits
- Competitive compensation programs.
- Flexible time off and leave policies.
- Comprehensive health and wellness coverage.
- Hybrid and flexible work arrangements.
- Employee referral and recognition programs.
- Professional development and learning support.
- Inclusive, collaborative team culture.
- Modern office spaces with team events and perks.
- Retirement and statutory benefits according to Indian regulations.
Skills
Java, Opensearch, Elasticsearch, Solr, Distributed Systems, AWS, Azure, Kubernetes, Python, Search Relevance, Learning To Rank, Data Consistency
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