About Manifest
Manifest OS is an AI-native company on a mission to replace the billable hour and make legal services more accessible for American businesses and consumers. We power the next generation of AI-native law firms with one unified global brand, a proprietary technology platform, and a centralized back office — enabling lawyers to eliminate the administrative burden and focus on delivering exceptional outcomes for their clients. Manifest OS has raised a $60M Series A from Menlo Ventures, Kleiner Perkins, First Round, and Quiet Capital.
About the Role
We're looking for a Design Engineer to help build the legal tech platform powering the next generation of AI-native law firms. You care as much about how software feels as how it works. You'll own the development of secure client portals and enterprise-grade systems - from architecture to production.
This opportunity is ideal for engineers who want broad scope, high ownership and move nimbly across lanes. You'll work across AI systems architecture and full-stack engineering - eval systems, retrieval, agent orchestration, and optimization, alongside the APIs, data models, and systems that power the core platform.
This is an in-person role - you'll be on-site at our NYC office 5 days a week.
What You’ll Do
Design Engineers here move across these areas as needed:
Design System Engineering
Evolve the design system into scalable components and tokens that make every project fast to ship and beautiful by default, whether a person or an agent is building it.
Spot patterns that keep recurring across the platform, and promote them into tested, documented primitives that designers and engineers can compose without reinventing.
Build the guardrails that keep the product on-system as it scales, including token linting, visual regression testing, and component documentation that AI coding tools can read and follow.
Product Engineering
Own features end to end, from the UI through the APIs and database tables behind it.
Build UI that holds up to production usage: failure modes, caching, accessibility.
Partner with design on what AI-native interfaces should be in a high-stakes domain: progressive disclosure, streaming states, and the patterns nobody's figured out yet
What We're Looking For
Must-haves:
7+ years building production software, with demonstrated depth in at least one area (frontend, distributed systems, ML/AI systems)
Proven track record delivering features that produce measurable business outcomes
Built or meaningfully shaped a production design system, including component APIs, tokens, theming, and documentation, that other engineers adopted and shipped with
Comfort with relational database design and data modeling
Fluent with AI coding tools as a core part of your daily workflow
A track record of self-teaching your way into unfamiliar systems and shipping there
First-principles and systems thinking: you can reason about a system you didn't build, from the database up through the API to the product surface
Familiarity with our stack - TypeScript, React, GCP, PostgreSQL
Nice-to-haves:
Deeply engaged with the AI tooling ecosystem - you follow new model releases, experiment with new tools as they land, and stay current out of genuine curiosity
Experience making a design system legible to AI coding tools, through machine-readable documentation, token linting, or visual regression testing that keeps generated UI on-system
Experience with eval systems, retrieval, agent orchestration OR ML in production
Background building client portals, CRMs, or case management systems
Familiarity with legal tech or other regulated industries
This is for you if....
You treat AI tools as core to how you architect and ship software. You have real depth in at least one area, plus the self-teaching ability to pick up unfamiliar systems and contribute there competently. You move with speed, thrive with ownership, and prefer outcomes over process. You want to build infrastructure that makes legal services more accessible to people.
This is not for you if....
You do your best work with clear processes and defined guardrails already in place. You're earlier in your journey with AI-augmented development and want more time to build that muscle first.