Ironclad
Senior Software Engineer, Agentic Search
- Location
- San Francisco, CA, US
- Arrangement
- Hybrid
- Employment type
- Full-time
- Level
- Senior
- Posted
- 18 September 2026 (12 days ago)
Checked todayApplications go to the employer, never to RoleSprint
About this role
Build AI contracting at enterprise scale. Ship it fast.
Ironclad is building AI on one of the most consequential datasets in enterprise software: over 2 billion contracts across thousands of the world's largest organizations. Contracts run every dollar, deal, and business relationship on the planet, and the AI transformation of this space is still largely uncharted. Engineers here are building agentic solutions to problems that haven't been solved yet, in a category that's still being defined. The feedback loop is short, the data is rich, and the people closest to the work are the ones deciding what gets built next. That ability to deliver impact quickly is why the the companies at the forefront of AI choose Ironclad to manage their contracts.
We’re consistently recognized as a leader in the industry: a Leader in the Forrester Wave and Gartner Magic Quadrant for Contract Lifecycle Management, a Fortune Great Place to Work, and one of Fast Company’s Most Innovative Workplaces. Ironclad has also been named to Forbes’ AI 50 and Business Insider’s list of Companies to Bet Your Career On. We’re backed by leading investors including Accel, Y Combinator, Sequoia, BOND, and Franklin Templeton. For more information, visit www.ironcladapp.com http://www.ironcladapp.com or follow us on LinkedIn.
This is a hybrid role. Office attendance is required at least twice a week on Tuesdays and Thursdays for collaboration and connection. There may be additional in-office days for team or company events.
ABOUT THE TEAM
At Intelligence Platform org, we own Ironclad's Agent Assistant, Conversational Search, and Content Understanding — the systems that help users and AI agents understand, find and act on the right contract information. These are the flagship AI capabilities of our product.
The team is a mix of ML and ML infrastructure engineers who build and operate these systems together.
WHAT YOU'LL WORK ON
- Agentic search systems: Evolve the architecture that combines LLM and retrieval system to produce optimal answer for complex or ambiguous questions.
- Eval-driven development: Design and run the benchmarks and experiments that measure search quality, and use that feedback to improve the system.
- Search quality: Contribute to the company's search quality bar.
- Content understanding & ingestion: turn raw documents into processed data that can be consumed by retrieval systems, by building/using NLP/LLM models and pipelines
WHO WE'RE LOOKING FOR
- 4 years experience building production systems, with hands-on experience in search, information retrieval, content understanding or recommendation systems at meaningful scale.
- Demonstrated expertise 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 workflow — offline benchmarks, regression detection, structured A/B comparison — as opposed to shipping and hoping.
- Strong ownership and communication.
- Care deeply about system scalability, reliability, and right design patterns.
- Comfortable operating in a dynamic, fast-paced and outcome-driven environment.
Base Salary Range: $180,000 - $200,000 offers company bonus
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.
Work location
- San Francisco, CA, US
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About this listing
Published on Ashby under the board identifier Ironcladhq, which is the name the employer’s own job board carries. RoleSprint has not verified the company’s registered or trading name, so it is shown exactly as published rather than tidied up.
RoleSprint is not the employer and not a recruiter. Applications are made on the employer’s own site and never reach us; what RoleSprint does is help you decide whether a role is worth your time and prepare for it if it is.
Published 18 September 2026, last checked today. A posting stops being advertised here 90 days after the employer published it, and one the employer takes down is marked closed rather than quietly removed.