Juliet

Experience: 8+ years, senior candidates only | Type: Full-time | Location: Remote (India)

 WHAT WE'RE BUILDING [See www.juliet.space]

 We're building Juliet — an AI that runs marketing end to end. Our users are marketers, founders and CEOs, growth leads, agencies, fractional execs, and SMBs —

 not developers. They tell Juliet the goal; she plans, writes production code, and ships real marketing — conversion-optimized websites, launch assets, campaigns,

 audits — autonomously.

 That's the engineering problem in one line: the humans in the loop can't read code, so the agent has to get it right on her own — plan, build, self-correct,

 recover, ship. Under the hood it's a browser-based studio backed by cloud sandboxes, a real-time streaming pipeline, and a LangGraph agent working across 83

 tools and 63 skill modules.

 Small team, big ambitions. You'll ship things users touch daily — not write JIRA tickets about them.

 THE ROLE

 We're hiring one architect-level engineer to lead Juliet's technical execution. You'll own the architecture end to end, set direction for a small dev team,

 review what ships, and still write code every day — a player-coach, working directly with the founder. Your calls on agent behavior, system design, and

 infrastructure become the product.

 THE STACK

 - Frontend: Next.js 15, React 19, TypeScript, Zustand, CodeMirror 6, XTerm.js

 - API: NestJS 11, Supabase, Redis, PostgreSQL, Server-Sent Events

 - AI agent: Python 3.11, LangGraph 1.x + LangChain, Anthropic / Google / OpenAI model providers

 - Infra: Modal cloud sandboxes, Docker, Netlify deployments

 - Monorepo: Turborepo, pnpm

 WHAT YOU'LL WORK ON

 → Agentic AI workflows — design and improve multi-step LangGraph agent graphs that plan, write code, run commands, and self-correct across 83 tools, 63 skill

 modules, and a 30+ stage middleware pipeline

 → Real-time streaming architecture — SSE pipelines that relay agent actions from the Python backend through NestJS to the browser, with reconnection, health

 monitoring, and interrupt handling (plan approvals, clarifying questions)

 → Agent execution environments — sandbox lifecycle management on Modal: file sync, terminal I/O, command execution, and live preview with per-asset esbuild

 bundling

 → State & memory systems — LangGraph Postgres checkpointers, middleware-injected context (goals, design docs, memory anchors), and conversation summarization

 → Marketing intelligence & asset engines — public AEO, CRO, and brand-perception audit pipelines (multi-engine LLM probing, streamed reports) and a 20-format

 marketing asset studio

 → Full-stack product features — collaboration (roles & permissions), the Netlify deployment pipeline, image handling, subscription/quota systems, and onboarding

 flows

 WHAT WE'RE LOOKING FOR

 Must-have:

 - 8+ years of professional software engineering experience — this is a senior seat; most people who thrive in it have closer to ten, including time as a tech

 lead or architect who owned a system end to end

 - Both worlds on your resume: engineering rigor inside a large company AND 0→1 ownership at an early-stage startup

 - Strong TypeScript and Python — you're comfortable shipping production code in both

 - Production agentic experience — you've built and operated LLM agent systems with LangGraph, LangChain, or similar: agent graphs, tool use, state management,

 prompt engineering, evals. Well beyond calling a chat endpoint.

 - AI-native development workflow — you drive Claude Code and Codex proficiently as everyday tools: agentic loops, skills, parallel sessions. You have opinions

 about working with coding agents because you do it daily.

 - Experience with React/Next.js and building complex, stateful UIs

 - Familiarity with real-time systems (SSE, WebSockets, streaming APIs)

 - Architect-level system design — you can own how data flows across four services and defend every tradeoff

 Strong plus:

 - Background in developer tools, IDEs, or coding platforms

 - Container runtimes and sandboxed execution (Modal, E2B, Firecracker)

 - NestJS or similar Node.js backend framework experience

 - Depth in PostgreSQL, Redis, and Supabase

 - LLM observability and evals (LangSmith or similar)

 - Exposure to marketing or growth products

 WHY THIS ROLE IS DIFFERENT

 You set the architecture. This isn't a feature factory, and you won't be implementing someone else's design doc. Technical execution is yours to lead.

 AI-native from day one. The agent isn't bolted on — she IS the product. You'll work at the intersection of LLM capabilities, agent infrastructure, and product

 design for non-technical users.

 Depth over breadth. The system spans cloud sandboxes, streaming infrastructure, agentic AI, and full-stack web — an IDE's internals where the only developer is

 the AI. There's always a hard problem to solve.

 Small team, big leverage. Your code ships fast and reaches users immediately. No layers of approval.

 HOW TO APPLY

 Send us:

 1. Your resume

 2. A short note on the most complex agentic system you've shipped — what broke, and what you'd redo

 3. Your AI coding setup: which tools you drive daily (Claude Code, Codex, other) and how

 4. (Optional) A link to something you've built that you're proud of