Staff/Senior Staff Software Engineer (Agentic Search)

Ironclad; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Dental, Vision & Health Insurance

401K

Wellness reimbursement

Flexible vacation policy

Parental leave

Work from home opportunities

Generous health benefits

Job summary

Ironclad is hiring for a Staff/Senior Staff Engineer on the Intelligence Platform team to own agentic search architecture, integrating LLMs with retrieval to answer complex contract questions. You will lead eval-driven development, set technical direction, and mentor engineers across AI teams.

You will partner with product and engineering leaders to raise search quality, drive architecture, and own content understanding pipelines that convert documents into usable structured data for retrieval

Qualifications

• 10+ years building production systems in search/information retrieval.
• Experience with LLMs, retrieval, and RAG architectures.
• Proven ability to drive architectural decisions and technical direction.
• Experience building eval-driven benchmarks and A/B workflows.

Responsibilities

• Own agentic search architecture, combining LLMs and retrieval to answer complex questions.
• Design and run benchmarks, experiments, and evaluation of search quality.
• Raise the company-wide search quality standard and influence others.
• Own content understanding and ingestion to feed retrieval systems.
• Set technical direction across AI org teams and mentor engineers.

Skills

Agentic Search

LLMs

Retrieval systems

Eval-driven development

Architectural leadership

Mentoring engineers

Education

MS in CS

BS in CS

Tools

Elasticsearch

OpenSearch

Solr

Python

Job description

• 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
• 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

Benefits

• Dental, and vision insurance
• 401K
• Wellness reimbursement
• Flexible vacation policy
• Generous parental leave for both primary and secondary caregivers
• Work from home opportunities
• Health insurance

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-offsDemonstrated depth in one of: learned/hybrid retrieval (lexical + vector + reranking), query understanding/NLU pipelines, or production LLM agent systems — ideally more than one10+ years building production systems, with a substantial portion in search, information retrieval, content understanding, or recommendation systems at meaningful scaleExperience with search frameworks (Elasticsearch or equivalent — Solr, Vespa, OpenSearch; embedding search) in production, including relevance tuning and rerankingComfortable operating in a dynamic, fast-paced, outcome-driven environmentStrong autonomy, ownership, and technical leadership across teams, including mentoring senior engineers and driving architectural decisionsExperience building eval-driven workflows — offline benchmarks, regression detection, structured A/B comparison — as opposed to shipping and hopingHands-on experience with post-training algorithms and infrastructure, including SFT and RLExperience with content understanding and/or information retrieval in structured-document-heavy domainsPrior work on RAG systems involving data sources in different formats (Google Docs, PDFs, DOCX, etc.)