Technical Lead – Full-Stack Development, AI

Description

• Lead the technical roadmap for generative AI integration across all product surfaces

• Drive adoption of agentic AI patterns and multi-agent systems within our platform

• Establish engineering best practices, code review standards, and development workflows

• Make critical technology decisions that will scale with 10x growth

• Build production-grade features using modern frameworks (React, Next.js, Node.js, Python)

• Integrate LLMs, vector databases, and RAG systems into customer-facing applications

• Optimize AI model inference and deployment pipelines for sub-200ms response times

• Implement real-time features using WebSockets, WebRTC, and event-driven architectures

• Lead and mentor a team across frontend, backend, and AI/ML

• Drive technical hiring and build processes to scale engineering

• Foster a culture of rapid experimentation, learning, and shipping quality code

• Collaborate with product, design, and business teams to align technical execution with company vision

Requirements

• 7+ years of full-stack development with recent experience in modern frameworks

• Deep expertise in TypeScript/JavaScript, Python, and at least one systems language (Go/Rust)

• Production experience with generative AI APIs (OpenAI, Anthropic, Google) and fine-tuning

• Hands-on experience building agentic AI systems and multi-agent workflows

• Strong background in distributed systems, microservices, and cloud architecture (AWS/GCP)

• 3+ years of technical leadership experience, preferably at high-growth startups (Series A-C)

• Track record of scaling engineering teams and systems through rapid growth phases

• Experience building 0-to-1 products with millions of users

• Strong product intuition and ability to balance technical debt with feature velocity

• Expertise in vector databases (Pinecone, Weaviate, Chroma) and embedding strategies

• Experience with AI evaluation frameworks and LLM observability tools

• Understanding of prompt engineering, RAG architectures, and model optimization

• Knowledge of transformer architectures and experience with fine-tuning workflows

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