Senior Software Engineer (Agentic Search)

• 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
• 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

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

• Demonstrated expertise in one of: learned/hybrid retrieval (lexical + vector + reranking), query understanding/NLU pipelines, or production LLM agent systems — ideally more than one
• 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
• Comfortable operating in a dynamic, fast-paced and outcome-driven environment
• Strong ownership and communication
• Experience building eval-driven workflow — offline benchmarks, regression detection, structured A/B comparison — as opposed to shipping and hoping
• Care deeply about system scalability, reliability, and right design patterns
• Experience with search frameworks (Elasticsearch or equivalent — Solr, Vespa, OpenSearch; embedding search) in production, including relevance tuning and reranking
• 4 years experience building production systems, with hands-on experience in search, information retrieval, content understanding or recommendation systems at meaningful scale