Staff/Senior Staff Software Engineer, Agentic Search

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. We have multiple roles open, and are hiring a range of levels — Staff and Senior Staff. As a Staff or Senior Staff Engineer, Agentic Search, you'll own the architecture that combines LLMs and retrieval systems to answer complex, ambiguous questions about a customer's contracts, and you'll set the technical direction that other engineers across the AI organization build on. You'll partner closely with product, applied science, and engineering leaders to raise the company's search quality bar, and you'll bring the technical depth and eval-driven rigor to turn ambiguous problems into shipped, measurable improvements. Scope and ownership will be calibrated to level.

Responsibilities

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. Design and run the benchmarks and experiments that measure search quality, and use that feedback to continuously improve the system; Raise the search quality bar. 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; Set technical direction. Define architectural decisions and technical direction that other engineers across the AI organization build on

Requirements

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

Nice 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.)

Benefits

100% health coverage for employees (medical, dental, and vision), and 75% coverage for dependents with buy-up plan options available; Market-leading leave policies, including gender-neutral parental leave and compassionate leave; Family forming support through Maven for you and your partner; Paid time off - take the time you need, when you need it; Monthly stipends for wellbeing, hybrid work, and (if applicable) cell phone use; Mental health support through Modern Health, including therapy, coaching, and digital tools; Pre-tax commuter benefits (US Employees); 401(k) plan with Fidelity with employer match (US Employees); Regular team events to connect, recharge, and have fun; Equity awards; Competitive health and wellness benefits; Commitment to career growth and development; Opportunity to help build the company you want to work at