Senior Staff Software Engineer, Agentic Search

About the role

Ironclad's Intelligence Platform team owns Agent Assistant, Conversational Search, and Content Understanding — the systems that help customers and AI agents understand, find, and act on the right contract information. These are the flagship AI capabilities of our product, built and operated by a combined team of ML and ML infrastructure engineers.

Qualifications

• 10+ years building production systems, with a substantial portion in search, information retrieval, content understanding, or recommendation systems at meaningful scale.
• Demonstrated depth 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 workflows — offline benchmarks, regression detection, structured A/B comparison — as opposed to shipping and hoping.
• Strong autonomy, ownership, and technical leadership across teams, including mentoring senior engineers and driving architectural decisions.
• Comfortable operating in a dynamic, fast-paced, outcome-driven environment.

Great to Have:

• Hands-on experience with post-training algorithms and infrastructure, including SFT and RL.
• 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.).

Scope and Ownership

Scope and ownership will be calibrated to level. You'll own agentic search architecture, design and evolve the systems that combine LLMs and retrieval to produce optimal answers to complex or ambiguous questions, drive eval-driven development, contribute to and influence the company's overall search quality standard, own content understanding and ingestion, turn raw documents into processed data that retrieval systems can consume, by building and using NLP/LLM models and pipelines, and own technical direction, define architectural decisions and technical direction that other engineers across the AI organization build on.

Base Salary Range

Senior Staff: $220,000 - $270,000