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Ironclad is building AI-powered contract management at enterprise scale, leveraging a dataset of over 2 billion contracts across thousands of the world's largest organizations. The company is recognized as a leader in the Contract Lifecycle Management space (Forrester Wave, Gartner Magic Quadrant) and has been named to Forbes' AI 50 and Business Insider's list of Companies to Bet Your Career On. Backed by leading investors including Accel, Y Combinator, and Sequoia.
In this role, you will lead a team of engineers building production generative AI systems. You'll combine hands-on technical leadership with people management, setting the technical direction for the team while growing the engineers on it.
Key responsibilities:
- Lead and grow a team of engineers, balancing hands-on technical leadership with people support
- Own the technical roadmap and quality bar for your team's systems
- Own business outcomes by partnering with product management and translating customer and business needs into technical deliverables
- Personally contribute direct technical output: write design docs, drive architectural decisions, and write production code for highest-leverage or highest-risk problems
- Stay close to the architecture and technical details to review design decisions, unblock engineers, and make prioritization calls
- Set and uphold engineering standards: code quality, testing, eval-driven development, and production monitoring for reliability and output quality
- Manage prioritization and tradeoffs across competing priorities, and coordinate with adjacent teams
- Hire, mentor, and develop engineers; run performance and career development for direct reports
Requirements:
- Proven experience leading engineering teams as a manager, with a track record of shipping production systems
- Strong technical background in generative AI / LLM-based systems, with expertise to provide technical depth and direction
- Ability to work directly as a technical contributor, creating designs and implementing solutions
- Experience operating production ML/LLM systems: eval-driven development, monitoring for reliability and output quality, and staged rollouts
- Past experience in one or more of: NLP, content/document understanding, search/retrieval, Agent framework, or LLM training infra/frameworks
- Track record of hiring, mentoring, and growing engineers, and navigating performance and leveling conversations
- Strong cross-functional partnership skills; comfortable setting technical roadmap with product, engineering leads, and company leadership
- Comfortable operating in dynamic, fast-paced, outcome-driven environment with ambiguity in scope
Great to have:
- Experience scaling a team through significant architectural transition
- Familiarity with canary rollouts for ML/LLM systems
