Python Full-Stack Engineer || San Francisco | On-Site || Direct Hire / Fulltime

Amtex Systems Inc is an information technology and talent solutions company offering talent and BI consulting to the companies in US for over 25 years.

Our solutions are designed to fill resource gaps, by providing the right candidates who deliver value to the organization. Our propensity to nurture and build strong relationships with our clients helps us better understand their business demands and gives us the ability to provide services that are on time and rise above the rest.

• 10+years React / TypeScript with shipped PRs or production product work
• Node or Python backend experience that carried real production traffic
• Built interaction-heavy UI: infinite canvas, editor, node graph, media tool, or live workflow surface
• Hands-on REST/WebSocket APIs, Postgres data modeling, Redis caching, and production monitoring

• Built canvas, editor, graph, node-based, or workflow-builder surfaces
• Integrated image, video, audio, or other long-running generation APIs with queueing/error recovery
• Managed latency, queueing, cancellation, retries, and error recovery so generation stayed stable under load
• Small-team daily shipping habit: write, test, deploy, read data, iterate
• Can explain and fix why a creative workflow feels slow, confusing, or fragile

• Real-time / multiplayer systems: WebSocket, CRDT, collaborative editor, or live state
• Has used or integrated AI-generation APIs for image, video, or audio
• Heavy user of generative AI tools with taste for creator workflows

• Less than 10 years of serious React / TypeScript product work
• Frontend-only career with no production backend ownership
• CRUD-only full-stack work with no interaction-heavy UI or async generation flow
• Cannot explain what makes a creative product interaction feel good or bad
• Remote-only preference for an on-site required role

• Own Client Art end-to-end: browser infinite canvas, node workspace, model integrations, collaboration, Recipes, backend APIs, and creator-facing production polish.

• 10+years of React / TypeScript production experience, provable in shipped PRs.
• Backend experience in Node or Python that has carried real production traffic.
• Hands-on product ownership of interaction-heavy UI: infinite canvas, node graph, workflow editor, live preview, media tool, or comparable surface.
• Can work across REST + WebSocket APIs, Postgres data modeling, Redis caching, production monitoring, and async generation flows.
• Experience wiring slow or failure-prone model/external API calls into a stable user experience: latency., queueing, cancellation, retries, and error recovery.
• High-agency daily shipping habit: write, test, deploy, read data, iterate without waiting on a weekly review.

• The node-based infinite canvas in React and TypeScript: drag, connect, live preview, multi-model result rendering, frame rate, and responsiveness that pass a picky designer's eye.
• The backend behind it: Node/Python, REST and WebSocket APIs, Postgres data modeling, Redis caching, production monitoring, and the first line of schema through live operations.
• Image, video, and audio model calls inside canvas nodes, with latency, queueing, cancellation, retries, and error recovery so one-click generate stays stable under load.
• Daily product iteration: write, test, deploy, read data, and iterate so creators can use this morning's idea by this afternoon.

• Real-time or multiplayer systems: WebSocket, CRDT, collaborative editing, or live state.
• AI generation APIs across image, video, audio, 3D, lipsync, upscaling, or other creative models.
• Heavy personal usage of generative AI tools and strong taste for creative workflows.

• The bet: AI creative production is moving from one-off prompts into reusable, collaborative workflows. Client wins if creators can turn an idea into images, video, audio, edits, and repeatable Recipes on one cloud canvas without managing models or GPUs.
• Cloud-native infinite canvas for image, video, audio, 3D, text, and tool nodes
• 100+ models from leading providers on one workspace, with side-by-side comparison and workflow chaining
• Reusable Recipes capture prompts, models, edits, and connections so creators can remix a style instead of rebuilding it
• Team collaboration, shared canvases, client Reel, and creator-led trend discovery are part of the product surface
• The bar is production creative flow: fast generation, clear failures, stable queues, good taste, and shipping experiments from data