Artificial Intelligence Engineer | Vesting | No Cash

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About Superdecision

Superdecision is an AI-native product execution platform that transforms decisions into deployable, scalable solutions. We are solving one of the most critical structural failures in the digital product lifecycle by building a unified Decision-to-Execution System.

The Role

We are looking for a Computer Science Engineer to design and implement the advanced algorithmic systems and platform intelligence that power SuperDecisione. You will sit at the intersection of research and engineering, translating complex computational models into production-grade systems running in a live, scaling SaaS product.

You will build the intelligence layer that makes every product decision structurable, traceable, and measurable , the technical backbone of our Decision Intelligence Layer.

Get things done:

• Lead AI infrastructure in production environments.
• Design and implement multi-agent systems with deep retrieval capabilities.
• Build robust context management systems that maintain design intent across sessions.
• Optimize agent coordination, communication patterns, and decision-making workflows.

Product And Research Integration

• Translate cutting-edge AI research into working features that designers actually use.
• Implement advanced retrieval-augmented generation (RAG) systems for design knowledge.
• Build context-aware agents that understand design patterns, user preferences, and project history.
• Work closely with founders and the early team to shape product direction.

Technical Leadership

• Drive core technical and product decisions around AI capabilities.
• Establish best practices for agent evaluation, monitoring, and continuous improvement.
• Scale AI systems to handle complex, multi-step design workflows.
• Own the full stack from model fine-tuning to production deployment.

Requirements

• Production AI Experience: Built AI agents in production with real users (web-socket, async, gRPC).
• Multi-Agent Systems: Experience implementing and evaluating complex agent architectures.
• Retrieval and Context: Deep experience with RAG systems, vector databases, and context management.
• Strong Engineering: Solid software engineering fundamentals with a focus on scalable, maintainable systems.
• Communication: Clear communication with engineers, designers, and non-technical stakeholders.

Nice To Have

• Experience with design tools, creative workflows, or visual AI.
• Like to do product thinking and how to shape the product.
• Previous startup experience in fast-paced, high-ownership environments.

Tech Stack You'll Work With

• AI/ML: OpenAI, Anthropic, or similar LLM APIs.
• Retrieval: Vector databases (Pinecone, Weaviate, Chroma).
• Backend: Python, HTTP/2 connections, async processing.
• Infrastructure: Cloud platforms (AWS/GCP), Docker, and monitoring tools.
• Tools: Cursor for development, internal tooling as needed.

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