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Staff/Senior Staff Software Engineer (Agentic Search)

Ironclad

Skills

Required

  • search / information retrieval / content understanding / recommendation systems
  • query understanding/NLU pipelines / production
  • reranking
  • learned/hybrid retrieval
  • vector
  • LLM agent systems
  • building production systems
  • search frameworks
  • Elasticsearch
  • Solr
  • Vespa
  • OpenSearch
  • embedding search
  • tuning

Preferred

  • RAG
  • Google Docs
  • PDFs
  • DOCX
  • measure search quality
  • modern LLM APIs

Join Ironclad's Intelligence Platform team as a Staff/Senior Staff Software Engineer (Agentic Search). In this role, you will own the architecture that combines LLMs and retrieval systems to answer complex questions about contracts. You will drive eval-driven development, raise the search quality bar, and own content understanding and ingestion. You will also set the technical direction for other engineers across the AI organization.

Responsibilities

  • Architect and evolve the systems that combine LLMs and retrieval to produce optimal answers to complex or ambiguous questions.
  • Design and run the benchmarks and experiments that measure search quality, and use that feedback to continuously improve the system.
  • Define architectural decisions and technical direction that other engineers across the AI organization build on.
  • 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 workflows — offline benchmarks, regression detection, structured A/B comparison — as opposed to shipping and hoping

Requirements

  • Demonstrated depth in one of: learned/hybrid retrieval (lexical + vector + reranking), query understanding/NLU pipelines, or production LLM agent systems — ideally more than one
  • 10+ years building production systems, with a substantial portion in search, information retrieval, content understanding, or recommendation systems at meaningful scale
  • Experience with search frameworks (Elasticsearch or equivalent — Solr, Vespa, OpenSearch; embedding search) in production, including relevance tuning and reranking
  • Comfortable operating in a dynamic, fast-paced, outcome-driven environment
  • Strong autonomy, ownership, and technical leadership across teams, including mentoring senior engineers and driving architectural decisions
  • Hands-on experience with post-training algorithms and infrastructure, including SFT and RL

Preferred

  • Experience with content understanding and/or information retrieval in structured-document-heavy domains
  • Prior work on RAG systems involving data sources in different formats (Google Docs, PDFs, DOCX, etc.)

Pay

USD 188,000 - 270,000