Agentic search systems: Evolve the architecture that combines LLM and retrieval system to produce optimal answer for complex or ambiguous questions.

Eval-driven development: Design and run the benchmarks and experiments that measure search quality, and use that feedback to improve the system.

Search quality: Contribute to the company's search quality bar.

Content understanding & ingestion: turn raw documents into processed data that can be consumed by retrieval systems, by building/using NLP/LLM models and pipelines

Who we're looking for

4 years experience building production systems, with hands-on experience in search, information retrieval, content understanding or recommendation systems at meaningful scale.

Demonstrated expertise in one of: learned/hybrid retrieval (lexical + vector + reranking), query understanding/NLU pipelines, or production LLM agent systems — ideally more than one.

Experience with search frameworks (Elasticsearch or equivalent — Solr, Vespa, OpenSearch; embedding search) in production, including relevance tuning and reranking.

Fluency with modern LLM APIs and multi-provider orchestration (Anthropic, OpenAI, Google) — reasoning about token budgets, provider-specific tool-calling semantics, and prompt-caching trade-offs.

Experience building eval-driven workflow — offline benchmarks, regression detection, structured A/B comparison — as opposed to shipping and hoping.

Strong ownership and communication.

Care deeply about system scalability, reliability, and right design patterns.

Senior Software Engineer, Agentic Search

Responsibilities

Qualification

Required

Benefits

Company

Ironclad HQ

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