Senior Staff Software Engineer, Agentic Search

Ironclad; San Francisco (CA); On-site; USD 220,000 - 270,000; Full time

Benefits offered by this job

Health coverage

Equity awards

Career growth opportunities

Job summary

Ironclad's Intelligence Platform team is hiring senior engineers to own agentic search architecture and content understanding, building systems that combine LLMs with retrieval to answer complex questions.

You will design eval-driven benchmarks, drive architectural decisions, and mentor engineers while shipping high-impact AI capabilities at scale in a fast-paced, outcome-driven environment.

Qualifications

• 10+ years building production systems.
• Deep experience in one of: learned/hybrid retrieval, query understanding, or production LLM agent systems.
• Experience with search frameworks (Elasticsearch, Solr, Vespa, OpenSearch; embedding search).
• Fluency with modern LLM APIs and multi-provider orchestration (Anthropic, OpenAI, Google).
• Experience building eval-driven workflows (offline benchmarks, AB tests).
• Strong autonomy, ownership, and technical leadership across teams.

Responsibilities

• Own agentic search architecture and evolve systems with LLMs and retrieval.
• Drive eval-driven development with benchmarks and experiments to improve search quality.
• Raise the search quality bar across the company’s standards.
• Own content understanding and ingestion using NLP/LLM models and pipelines.
• Set architectural direction and influence engineers across the AI org.

Skills

Production systems

Search/IR

LLM APIs

Technical leadership

Tools

Elasticsearch

OpenSearch

Solr

Vector search

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.

What You’ll Do

• 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.

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.).

Base Salary Ranges

• Senior Staff: $220,000 - $270,000

The base salary range represents the minimum and maximum of the salary range for this position based at our San Francisco headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of Ironclad’s competitive total rewards package, which also includes equity awards (a new hire grant, along with opportunities for additional awards throughout your tenure), competitive health and wellness benefits, and a commitment to career growth and development.

US Full-Time Employee Benefits at Ironclad:

• 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

And most importantly: the opportunity to help build the company you want to work at.

UK Employee-specific benefits are included on our UK job postings.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.