KINDA · Open role
Tech Lead
Design and build the technical system that powers KINDA — turning an abstract loop of action, data, and content into a scalable, reliable platform.
- Fractional founder role · keep your current job
- ~20% equity · standard vesting and contribution terms
- Founding team of a company being built from day one
Role summary
An AI-native systems role across backend, data, and multimodal AI.
This is not a standard engineering role.
You will turn an abstract system — where real-world actions become data and content — into a scalable, reliable platform that combines backend, frontend, data pipelines, and multimodal AI.
Engagement model
Designed as a fractional founder position.
In return, you receive ~20% equity, subject to standard vesting and contribution terms.
For details on structure, time commitment, and conditions, refer to the FAQ.
- You do not need to leave your current job.
- You contribute part-time, focused on architecture and key technical decisions.
- You work as part of the founding team of the company.
What you'll be building
The full technical system behind the loop: action → proof → data → content → distribution → new action.
- Infrastructure to capture real-world actions — media, inputs, metadata.
- Pipelines to process and validate evidence at scale.
- Systems that structure data from unstructured inputs.
- AI workflows that generate video, images, and text from validated actions.
- Distribution and performance tracking across platforms.
Core responsibilities
- Define and own the system architecture end-to-end.
- Build and scale backend systems and APIs.
- Design data pipelines for processing images, videos, and user inputs.
- Integrate and optimize LLMs and multimodal models.
- Implement AI pipelines for content generation (video, image, text) and content analysis (vision, tagging, classification).
- Build frontend systems where needed — product UX and internal tools.
- Ensure performance, scalability, and reliability of the platform.
What we are NOT looking for
- Engineers who only execute tickets.
- Specialists who cannot operate across the stack.
- People without experience working with AI systems.
- People who rely on predefined architectures instead of designing systems.
Required profile
- Strong full-stack engineering background.
- Proven experience building platforms, not just features.
- Experience working with AI systems — LLMs, APIs, or custom pipelines.
- Ability to operate with high autonomy in undefined environments.
Key capabilities
System architecture, AI & LLMs, multimodal & vision, content generation, product integration.
System Architecture — design scalable, modular systems; experience with backend architectures, APIs, and distributed systems; understanding of data flow from ingestion to processing to output.
AI & LLMs — integrate and optimize LLMs; understand prompt design, context management, and cost/performance trade-offs; build workflows around AI models, not just call APIs.
Multimodal & Computer Vision — work with image and video processing pipelines; understand tagging, classification, and feature extraction; convert unstructured media into structured data.
Content Generation Systems — experience with video and image generation tools or pipelines; orchestrate multiple AI services into a single workflow; manage latency, cost, and scalability constraints.
Frontend & Product Integration — build or support frontend layers when needed; product-driven engineering; experience with internal tools and user-facing platforms.
Why this role is hard
You are not building a typical SaaS.
This requires combining backend, AI, and media systems into one coherent architecture.
- Inputs are messy, real-world human actions.
- Data must be validated and structured.
- Outputs are AI-generated content at scale.
Why it matters
KINDA connects real action, data, AI content, and distribution.
The technical system is the product.
- Real-world actions.
- Structured, auditable data.
- AI-generated content.
- Social distribution systems.
Success looks like
- A robust backend capable of handling real-world inputs at scale.
- Reliable pipelines for processing and validating media.
- Efficient AI workflows for generating and analyzing content.
- A system that supports a self-reinforcing loop between action, content, and distribution.
Ideal background
- Senior or Staff engineer in platform or AI-native products.
- Experience in startups or high-ownership environments.
- Exposure to computer vision, generative AI, or media systems.
- Comfortable working across backend, frontend, and AI layers.
"Build the system that turns real-world actions into data, and data into scalable content."
Apply to this role
Build Tech Lead at KINDA.
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