Labrynth accelerates progress by streamlining regulatory complexity. We build AI-powered platforms that navigate complex regulations, generate audit-level documentation, and provide certainty, not shortcuts. Our technology serves clients across heavily regulated industries including energy, compliance, and government regulations.
We operate as a forward-deployed engineering organization: small, high-velocity teams embedded directly with clients to rapidly discover needs and ship production-quality solutions.
About the RoleWe're building the next product in this line: an invite-only B2C platform for personal and team accounts, developed as a greenfield product alongside the current application in the patent/IP space.
We're looking for a Front End Engineer to own the client-facing B2C experience end to end: invited-account onboarding, account and membership UX, a guided exploration experience built over our workspace/exploration/idea/draft model, and durable-operation progress UI — all built entirely against our generated BFF client, and all built to hold up in live prospect and partner demos.
This is a contract engagement (Agency / Statement of Work), with an initial term of 60–90 days and the option to extend. You'll report to the Patent Project engineering lead and coordinate closely with Backend, DevOps/Platform, Security, our Product designer, and QA.
A note on the architecture: identity runs through Amazon Cognito (customer pool: email/password + Google federation, PKCE), with customer sessions as opaque, HttpOnly/Secure cookies issued by our BFF. The TypeScript BFF is the sole authorization, capability, entitlement, and domain-mutation boundary — the frontend is a presentation and interaction layer that consumes generated OpenAPI clients only, even for server-rendered calls. The frontend holds no database, Neo4j, S3, Stripe-secret, queue, model-provider, or worker credentials. Private customer data lives in PostgreSQL and S3; Neo4j holds only the shared public patent corpus. During closed beta, payment is disabled by configuration, and entitlements resolve through a capability matrix.
Immediate deliverables (first 2–4 weeks)
Wire up the BFF client: consume the checked OpenAPI contract via generated clients, and establish stable success/error envelopes, request IDs, idempotency-key and If-Match plumbing, and loading/empty/error/permission state scaffolding.
Build invited sign-in and account context: Cognito sign-in (email/password + Google, PKCE) wired to opaque BFF sessions and protected routes, with explicit account-context switching on staging.
Stand up the guided-exploration entry point: exploration create/run UI wired to the agent and the public corpus, showing the operation lifecycle via resumable SSE on staging.
Conduct a UX & code audit: review for correctness, performance, and consistency; produce a prioritized fix list and a design-system alignment plan.
60–90 day scope
Invited-account onboarding: invitation acceptance (personal signup / team membership), first workspace creation, first source upload with visible quarantine states (upload_pending → quarantined → processing → available|rejected|processing_failed), and ToS/legal-disclosure acceptance.
Account & membership UX: personal/team accounts, owner/member capabilities via capability policy v1, membership states, and guarded personal↔team conversion flows, with the active account always explicit and never inferred.
Guided exploration experience: the primary entry point over the workspace/exploration/idea/draft model, surfacing exploration lineage (derived_from / incorporates / branches_from / supersedes) and the operation lifecycle (accepted → dispatched → executing → succeeded|failed|cancelled|expired); raw model chain-of-thought is never shown.
Durable-operation progress: fetch-based resumable SSE (auth via header, cookie, or storage; reconnect replays from the last-seen event sequence; respect streams/session and account limits), with cursor-polling fallback and 409 cursor_expired snapshot/resync.
Public graph & analysis views: production-quality visualization and core claims/novelty/cluster views over the public reference plane.
Billing UI (beta): Stripe test-mode plan selection and entitlement display, with no live charging.
Performance & robustness: meet agreed Core Web Vitals budgets; consistent loading/empty/error/permission states; responsive and accessible UI.
Test coverage & handover: component and E2E coverage for critical paths, documented component patterns, and clean handover.
Ownership boundary: You own consumption of the generated OpenAPI clients over account-scoped routes (idempotency keys, ETags/If-Match, the 202 Accepted + operation_id pattern), the Cognito browser sign-in flow, the invited-account onboarding journey, account & membership UX, the guided exploration experience, durable-operation progress via resumable SSE, the payment beta plan/entitlement UI, design-system-driven UI (dark-first, black + red brand, semantic tokens), and component/E2E test coverage. You do not own or have direct authority over the database — that's coordinated with Backend, DevOps, Security, the Product designer, and QA.
Explicit non-goals:
No direct access to the database, Neo4j, S3, Stripe secrets, queues, model providers, or workers — everything goes through the BFF.
No implementing authorization/capability/entitlement policy (owned by BFF/Backend).
No private customer data in any graph view (Neo4j is public-only).
No building against the legacy Supabase auth model or the legacy law-firm/company account model.
Deep experience with React & Next.js, including Next.js (App Router) as a containerized service, server components, routing, and SSR that calls an internal API rather than data stores directly.
Contract-first client consumption: experience consuming generated OpenAPI/TypeScript clients in a pnpm monorepo, including idempotency keys, ETag/If-Match concurrency, and 202+operation polling, treating the BFF contract as the sole data authority.
Streaming UI experience: building guided/streaming agent interfaces on fetch-based resumable SSE (header auth, reconnect from last-seen sequence, stream limits) with cursor-polling fallback and 409 resync.
Identity-aware UI: experience handling Cognito-backed opaque BFF sessions, protected routes, and explicit account-scoped context on the client.
Data-dense & public-graph UX: experience building dashboards over search, claims/citations, clusters, and validation results, and interactive visualization of large, public reference data sets.
UI & styling: strong Tailwind skills and experience building component-driven UI from a design system and semantic tokens, not ad-hoc styles.
Performance & quality: solid grasp of Core Web Vitals, bundle size, and rendering performance, plus component and E2E testing and accessibility fundamentals.
Availability with meaningful overlap with US and Australian project hours for weekly sync and incident response.
Experience with graph visualization libraries for large citation/cluster networks.
Experience building onboarding flows with file-upload quarantine UX and legal-disclosure/ToS acceptance capture.
Experience with large data-set virtualization and rendering performance.
A track record of contributing reusable primitives back to a shared design system.
High-impact work at the intersection of AI and critical infrastructure regulation
Direct customer exposure and a seat at the table when we decide what to build
Small team with outsized influence; your field learning shapes the product roadmap
Modern AI-native development environment (Claude Code, Cursor, multi-model orchestration)
Remote-first
Competitive compensation
Character: integrity and trustworthiness above all
Competency: evoking trust and reliably delivering
Togetherness: family-level support and alignment
Impact: meaningful outcomes over activity
Commitment: ownership and follow-through
What’s In It For You
Labrynth is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Hourly rates are determined based on factors such as location, relevant experience, skills, internal pay equity, and market conditions.
During the interview process, your Talent Acquisition Partner will confirm the hourly rate range applicable to your location. For contractors outside the U.S., compensation is aligned with local market conditions and cost of living.
While every engagement is unique, our compensation philosophy is designed to ensure fairness, consistency, and competitiveness across Labrynth. Additional details regarding compensation, contract terms, and the scope of the engagement will be discussed throughout the hiring process.
Equal Opportunity Statement:
We’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law.
Skills Required
- Deep experience with React and Next.js (App Router, server components, SSR)
- TypeScript and consumption of generated OpenAPI TypeScript clients in a pnpm monorepo
- Contract-first client patterns: idempotency keys, ETag/If-Match concurrency, 202 + operation polling
- Streaming UI experience: fetch-based resumable SSE, reconnect from last-seen sequence, cursor-polling fallback, 409 resync
- Identity-aware UI: Amazon Cognito integration (email/password + Google federation, PKCE), opaque BFF sessions, protected routes
- Experience building data-dense dashboards and public-graph UX (search, claims/citations, clusters, validation views)
- Strong Tailwind CSS skills and component-driven UI from a design system using semantic tokens
- Performance & quality focus: Core Web Vitals, bundle size, rendering performance, accessibility, component and E2E testing
- Availability with meaningful overlap with US and Australian project hours
- Experience with graph visualization libraries for large citation/cluster networks
- Experience building onboarding flows with file-upload quarantine UX and legal-disclosure/ToS acceptance capture
- Experience with large data-set virtualization and rendering performance optimizations
- Track record contributing reusable primitives to a shared design system
What We Do
Infinity incubates companies focused on AI service businesses, combining repeat founders with world class applied AI engineers creating the next generation of service industries.








