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Founding Engineer — Full Stack (Backend + AI / Infrastructure Focus)

Open 17d

Summary

Builds the core AI-powered backend and real-time infrastructure for a video-based emotional performance coaching platform, integrating multimodal models, iOS-native systems, and scalable cloud services.

About the Role

Scivora is building a new category in emotional performance intelligence. Our early users—actors, performers, speakers, and founders—rehearse live on camera and receive real-time multimodal feedback on clarity, emotional delivery, presence, and communication patterns.

We are hiring one of two Founding Full-Stack Engineers , with this role leaning deeply into backend architecture, AI pipelines, native iOS-integrated real-time systems, and infrastructure scalability. You will build the core intelligence layer and technical backbone that powers the entire Scivora platform.

This is not a task-execution role. This is a founding technical partner role for an engineer who wants ownership, range, and the opportunity to architect a category-defining product from day zero and grow into long-term technical leadership.

Definition of Full-Stack at Scivora

At Scivora, “full-stack” means mobile + backend + AI :

  • Native iOS surfaces (Swift, SwiftUI, AVFoundation, camera frameworks)
  • Backend systems and APIs (Node, Python, distributed services)
  • AI pipeline integration (multimodal models, LLMs, inference orchestration)

What You Will Do

Backend + AI + Real-Time Infrastructure (Primary Focus)

  • Architect and implement Scivora’s backend systems (Node, Python)
  • Build and scale multimodal AI pipelines (vision, audio, NLP, behavioral feature extraction)
  • Integrate real-time feedback systems across iOS and cloud using WebRTC, WebSockets, and streaming protocols
  • Implement model routing, inference orchestration, and LLM-powered analysis
  • Design and optimize the emotional performance scoring engine (fusion models, scenario evaluation, context-aware feedback)
  • Own database modeling, authentication, user state, and session lifecycle management
  • Build secure, high-performance camera video ingestion and processing flows for live rehearsal
  • Optimize real-time emotional feedback rendering performance across mobile and network layers
  • Establish observability, monitoring, performance tuning, and system reliability
  • Deploy and manage infrastructure using Kubernetes, Terraform, or equivalent IaC tools

Full-Stack Mobile Responsibilities (Secondary but Required)

  • Support native iOS frontend engineering for UX/UI
  • Build internal dashboards and early user-facing tools
  • Implement limited frontend flows as needed
  • Collaborate with the frontend / product founding engineer on clean interface contracts between mobile, backend, and AI layers
  • Participate in and influence system-wide architectural decisions

Ideal Background

  • 5+ years of engineering experience across backend systems, distributed infrastructure, and AI/ML
  • Advanced proficiency in Python and Node/TypeScript
  • Experience with PyTorch, transformers, computer vision, and audio pipelines
  • Strong real-time systems experience (WebRTC, WebSockets, low-latency streaming)
  • Deep AWS or GCP cloud architecture experience
  • Strong understanding of camera systems, video pipelines, and mobile performance constraints
  • Proven ability to translate ambiguous founder vision into scalable, production-ready systems

Who You Are

  • A founder-minded engineer who wants to build the core engine of a new category
  • Equally comfortable moving fast in v1 and architecting for long-term scale
  • Fluent in technical reasoning and product trade-offs
  • Low-ego, high-range, resilient, and highly communicative
  • Motivated to grow into long-term technical leadership based on performance and fit

Compensation & Growth

  • Initial engagement will begin as a paid contract, structured to validate technical and team fit
  • Full-time salary will transition in once both sides confirm long-term alignment and production stability
  • Equity is offered as RSUs (Restricted Stock Units) based on role scope, ownership, and long-term impact
  • Compensation structure is flexible and competitive, aligned to experience and responsibility
  • This role is designed with a clear path into long-term technical leadership as Scivora scales

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

Technology, Information and Internet

See also

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