Founding AI Engineering Lead in NYC

Start: ASAP

TL;DR

🤝 Founding AI engineer in a leading tech role

💰 Competitive base salary + significant equity stake

💼 100+ paying customers, strong 6-digit ARR

🧠 Building the context engine for the agentic era

🤖 AI-native: you orchestrate agents, you don't just write code

📍 New York City - in-office

💼 Backed by unicorn founders, Axel Springer & Porsche

About

At Along AI, we are building the modern context engine, the persistent infrastructure layer that sits between an organization's knowledge and every AI system it uses.

As a Founding Engineer, you'll shape not just what we build, but how. We work in-office in New York City, move fast, and ship together.

The problem The bottleneck for AI in business was never intelligence. It was memory. It was context.

Teams copy-paste background into prompts, rebuild instructions for every tool, and watch agents go off the rails because they lack institutional knowledge. Today's AI stack has a gaping hole between raw data and capable models, no persistent understanding, no living memory that compounds over time. RAG is a runtime patch, not a solution.

Our solution: the Context Engine

Along AI connects to your systems of record, extracts the knowledge that matters, and organizes it into Kontext Keys — secure, self-contained units of context for a specific use case. One API serves Claude, ChatGPT, your own agents, or any tool in your stack. The same living knowledge graph powers all of them.

Behind every Kontext Key is a GraphRAG-powered knowledge graph — not a flat vector database, but a structured representation of your organization's entities, relationships, and processes. Context that compounds with every interaction.

What AI-native engineering means here

Orchestration over implementation — you direct agent pipelines, pick the right models, architect systems. Writing from scratch is the exception.

Context engineering — you design retrieval systems, memory layers, and structured context pipelines.

Eval-driven — evals before features. AI output quality is an engineering problem.

Prompt as code — versioned, tested, treated with full engineering rigor.

What we're looking for

✅ Systems thinker - you architect before you implement

✅ Hands-on LLM experience: GraphRAG, agent frameworks, prompt engineering

✅ Comfortable directing AI coding agents and reviewing output at speed

✅ Strong backend foundation: Node.js/TypeScript, API design, GCP/AWS

✅ Experience with knowledge graphs, vector DBs, and retrieval systems

✅ Shipped production AI features - not just prototypes

✅ 3–5+ years engineering experience, ideally at an early-stage startup is a plus

✅ Excited to work in-office in New York City

Our offer

Competitive base + significant founding equity (4yr vest, 1yr cliff)

In-office in New York City

Direct access to founders, full ownership of technical direction

25 days PTO

ISO27001, SOC2, GDPR compliant

"Working at Along feels like being part of a band at Glastonbury 🥁"

At Along AI, if you're excited about this role but don't tick every box - apply anyway.