Founding Engineer - Emerging Tech Sports Engagement Platform

Founding Engineer - Sports Engagement Platform
Location: Remote or Hybrid (flexible for the right candidate)
Core Responsibilities
1. Distributed Systems Architecture (Primary Focus)

• Design and implement high-scale distributed systems for real-time sports content delivery.
• Build event-driven microservices architectures supporting millions of concurrent users.
• Develop distributed caching, replication, and fault-tolerant systems for live sports events.
• Implement recommendation and personalization engines with sub-second latency.

2. Agentic AI & ML Systems

• Architect multi-agent AI systems for contextual understanding of sports data.
• Build production LLM inference pipelines (Claude, GPT-4, Hugging Face, Eleven Labs, and custom models).
• Design intelligent routing systems between AI models based on query complexity.
• Implement real-time context generation and personalization pipelines.
• Create and optimize vector search systems for knowledge retrieval and recommendations.

3. Visual Search & Content Understanding

• Develop visual recognition systems for sports plays, players, and moments.
• Implement Pinterest-style visual discovery experiences for sports content.
• Build multi-modal pipelines for text, video, and image understanding.
• Create personalized content recommendation systems based on visual preference data.

4. Platform & Infrastructure

• Lead core technical architecture for all 0-1 product development initiatives.
• Build secure, scalable payment and subscription systems.
• Implement real-time analytics, telemetry, and behavioral data infrastructure.

Required Experience
Essential Background

• 5+ years designing and scaling distributed systems (experience at large-scale consumer or social platforms ideal).
• 2+ years in technical leadership or serving as the senior technical owner on major projects.
• Demonstrated 0-1 product experience-built systems from scratch that reached millions of users.
• Hands-on experience deploying and optimizing ML/AI models in production environments.
• Experience building agentic or autonomous AI systems with real-time inference or decision-making.

Technical Stack Requirements

• Backend: Python (FastAPI, Django), distributed systems patterns, microservices.
• AI/ML: PyTorch or TensorFlow, LLM integration, vector databases, real-time inference pipelines.
• Infrastructure: AWS (at scale), Docker/Kubernetes, Elasticsearch.
• Databases: PostgreSQL, Redis, Neo4j, vector DBs (e.g., Pinecone, Weaviate).
• Frontend: React/TypeScript (collaboration expected, not primary focus).

Specific Experience Sought

• Built recommendation systems serving millions of users.
• Scaled real-time content delivery systems.
• Implemented visual search or content understanding pipelines.
• Led core architecture decisions in fast-growth environments.
• (Preferred) Experience in sports, media, or social engagement platforms.

What You'll Build
Year 1 - Foundation:

• Multi-agent AI system for contextual sports understanding.
• Distributed recommendation engine for personalized content.
• Real-time event processing and content generation systems.
• Visual search and discovery capabilities.
• Core platform supporting 100K+ active users.

Year 2+ - Scale:

• Infrastructure supporting millions of concurrent sports conversations.
• Advanced visual discovery and recommendation features.
• Analytics platform for enterprise and partner insights.
• Global scaling and internationalization infrastructure.

Why This Role Matters
You'll define the technical architecture for a platform that reimagines how sports fans engage with content-accessible without being condescending, contextual without being overwhelming. The product is backed by experienced consumer tech and sports industry leaders and is positioned within a $36B sports engagement market.

This is a rare opportunity to build the technical future of how fans connect with sports, from first principles.