Lead Software Engineer - AI
Company: Icertis
Location: New York, NY, United States
Salary: $200k per year
Type: Full-time
Posted: 2026-09-28
About this role
At Icertis, we’re transforming how enterprises manage contracts by applying AI to make them more intelligent, actionable, and impactful across the business.
With the acquisition of Dioptra, we are accelerating this vision by integrating advanced AI agents that fundamentally change how contracts are reviewed, analyzed, and understood. Together, Icertis and Dioptra are delivering an AI-first contracting experience used by some of the world’s largest and most complex enterprises.
On this team, you’ll:
- Report directly with Dioptra’s founders as part of a small, highly focused product and engineering group
- Build and evolve front-end experiences that bring powerful AI capabilities to life for end users
- Design intuitive, high-quality interfaces used by global enterprises such as Microsoft, Johnson & Johnson, and Mercedes-Benz
- Have meaningful ownership and influence over the user experience and product direction
- Join the enterprise legal technology market at a pivotal moment, with the opportunity to shape how AI is applied at scale
You may be a good fit for this role if:
- You have 5+ years in full-stack development, covering both front-end and back-end technologies.
- Experience working at a startup is a plus
- You are comfortable working on challenging problems, in ambiguous, rapidly changing environments.
- You want to have a large impact on the business as an early member of the team.
- You are using AI coding tools (cursor / codex) on a daily basis
- You have professional experience with the following technologies (must haves): client and server-side JavaScript/TypeScript, react, Python, SQL, databases, CI/CD, git, Gen AI models from OpenAI / Anthropic
Salary range and description
Min $200,000 - Max $300,000 USD per year
We are considering Engineers at various levels based on experience, thus the broad base salary range. Pay offered will vary based on job-related factors such as location, experience, training, skills, and abilities.
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