Senior Backend and Data Developer ([email protected])

• Experience in Python
• Experience in any Framework like Django, and Flask.
• Primary and Secondary skills - Python, OOPs and Data Structure
• Good understanding of Rest Api 
• Familiarity with event-driven programming in Python 
• Good analytical and troubleshooting skills

1. Proficiency in Python 3.x based web and backend development

2. Solid understanding of Python concepts

3. Experience with some form of Machine Learning (ML)

4. Experience in using libraries such as Numpy and Pandas

5. Some form of experience with NLP and Deep Learning using any of Pytorch, Tensorflow, Keras, Scikit-learn or similar

6. Hands on experience with RDBMS such as Postgres or MySQL

7. Experience building REST APIs using DRF or Flask

8. Comfort with Git repositories, branching and deployment using Git

9. Working experience with Docker

10. Basic working knowledge of ReactJs

11. Experience in deploying Django applications to AWS,Digital Ocean or Heroku

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

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 WHAT WE'RE BUILDING

 See http://www.juliet.space

 We're building Juliet, an AI that runs marketing end to end. Our users are marketers, founders, CEOs, growth leads, agencies, 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: a browser-based studio backed by cloud sandboxes, a real-time SSE streaming pipeline, and a LangGraph agent working across 83 tools and 63 skill

 modules. The agent isn't bolted onto the product. She is the product.

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

 ---

 THE ROLE

 We're hiring one architect-level backend engineer to own Juliet's agentic infrastructure end to end. That means the agent graph, the execution environment, the

 streaming pipeline, the state and memory systems — and setting technical direction for the engineers working alongside you.

 This is a player-coach seat. You'll still write code every day, and your architectural calls become the product. You'll work directly with the founder. No PMs in

 between.

 Frontend is part of the system. You won't be leading it, but you'll need to understand how the agent's output reaches the browser and be able to ship full-stack

 features when needed.

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 THE STACK

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

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

 Infra (primary): Modal cloud sandboxes, Docker, Netlify deployments

 Frontend (secondary): Next.js 15, React 19, TypeScript, Zustand, CodeMirror 6, XTerm.js

 Monorepo: Turborepo, pnpm

 ---

 WHAT YOU'LL WORK ON

 The majority of your time is here:

 Agentic AI workflows — Design, extend, and harden the LangGraph agent graph: multi-step planning, code generation, tool dispatch, self-correction, and recovery

 across 83 tools and 63 skill modules. This is the core of the product.

 Real-time streaming architecture — The SSE pipeline that carries every agent action from the Python backend through NestJS to the browser: event framing,

 reconnection, health monitoring, interrupt handling for plan approvals and clarifying questions.

 Agent execution environments — Sandbox lifecycle on Modal: container spin-up, file sync, terminal I/O, command execution, and live preview with per-asset esbuild

 bundling. The agent lives here.

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

 the agent knows what it knows.

 Backend API and data layer — NestJS services, Supabase schema, Redis caching, quota enforcement, webhook handling. The plumbing the agent depends on.

 Marketing intelligence pipelines — AEO, CRO, and brand-perception audit engines: multi-LLM probing, parallel inference, streamed structured reports, result

 caching. Audit-at-scale infrastructure.

 The remaining ~25% of your time:

 Full-stack product features — Collaboration (roles and permissions), the Netlify deployment pipeline, subscription and quota flows, onboarding. You'll ship these

 end to end — backend first, frontend to close the loop.

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 WHAT WE'RE LOOKING FOR

 Must-have:

 - 8+ years of professional software engineering, including meaningful time as a tech lead or systems architect who owned something end to end. Closer to ten is

 the norm for people who thrive here.

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

 - Production agentic systems experience. You've built and operated LLM agent systems in production with LangGraph, LangChain, or equivalent — agent graphs, tool

 use, state management, prompt engineering, evals. This means well beyond calling a chat endpoint.

 - Strong Python. You design and ship production Python daily. The agent codebase is yours to own.

 - Architect-level system design. You can own how data flows across four services, make tradeoffs under uncertainty, and defend every call.

 - AI-native development workflow. You drive Claude Code, Codex, or similar agentic tools as everyday instruments — not occasionally. You have opinions about

 working with coding agents because you do it constantly.

 - Real-time backend systems. You've built SSE, WebSocket, or streaming API infrastructure in production — not just consumed it.

 - Strong TypeScript. The API layer and most product features are in TypeScript. You're productive in it.

 Strong plus:

 - Background in developer tools, IDEs, or coding/execution platforms

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

 - Depth in PostgreSQL, Redis, and Supabase

 - LLM observability and evals tooling (LangSmith or similar)

 - NestJS or equivalent Node.js API framework experience

 - React/Next.js — enough to ship a full-stack feature without handoff

 - Exposure to marketing, growth, or publisher-facing products

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 WHY THIS ROLE IS DIFFERENT

 You own the architecture. Not a feature factory. Not someone else's design doc. The technical execution of an AI product is yours to lead.

 The agent is the product. You're not adding AI to an existing system. You're building and operating the system that is the AI. Every architectural decision

 touches what Juliet can and can't do.

 Hard problems, always. The system spans cloud sandboxes, streaming infrastructure, multi-step agent graphs, and a full-stack web product — for non-technical

 users who can't course-correct a broken output. The bar is high.

 Small team, real leverage. Your code ships to users the same week. No layers of approval.

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 HOW TO APPLY

 Send us:

 1. A short note on the most complex agentic system you've shipped: what broke, and what you'd redo. A link to something you've built that involves agent graphs, tool use, or autonomous multi-step execution

 2. What is one thing you would improve about Juliet? It could be a feature or a bug.

Develop, record and maintain cutting edge web-based J2EE, JAVA applications.

Experience on Java Spring Framework is required.

Experience on Hibernate is required.

Experience on REST Services is required.

Object-oriented programming, design, and patterns.

Strong proficiency with:Relational database concepts and data modeling.

Good communication skills to interact with customer, understand their requirement, effectively record the requirement and implement the same. 

Role / Purpose - Lead Developer - API and Microservices

Must have a strong hands-on development track record building integration utilizing a variety of integration products, tools, protocols, technologies, and patterns.

• Must have an in-depth understanding of SOA/EAI/ESB concepts, SOA Governance, Event-Driven Architecture, message-based architectures, file sharing, and exchange platforms, data virtualization and caching strategies, J2EE design patterns, frameworks
• Should possess experience with at least one of middleware technologies (Application Servers, BPMS, BRMS, ESB & Message Brokers), Programming languages (e.g. Java/J2EE, JavaScript, COBOL, C), Operating Systems (e.g. Windows, Linux, MVS), and Databases (DB2, MySQL, No SQL Databases like MongoDB, Cassandra, Hadoop, etc.)
• Must have experience implementing API Service architectures (SOAP, REST) using any of the market-leading API Management tools such as Apigee and frameworks such as Spring Boot for Microservices
• Should have Advanced skills in implementing API Service architectures (SOAP, REST) using any of the market-leading API Management tools such as Apigee or similar frameworks such as Spring Boot for Microservices 
• Appetite to manage large-scale projects and multiple tracks
•  Experience and knowhow of the e-commerce domain and retail experience are preferred

# Responsibilities:

• Build the APIs and internal mechanisms of the backend across all our services.
• Architect and provide guidance on building end-to-end systems optimized for speed and scale.
• Build and lead engineering teams to achieve product roadmap milestones.
• Oversee the research and development of new products and technologies.
• Engage with inspiring designers and front-end engineers, and collaborate with leading back-end engineers as we create reliable APIs
• Represent and evangelize engineering team in events, talks, conferences, etc.
• Be available for troubleshooting in case of backend emergencies.

# Requirements:

• Bachelor's in Computer Science or any Engineering domain with experience in Software Programming.
• 2-5 years of experience building large-scale software applications.
• Highly proficient with Java and knowledge of the many intricacies of Spring Boot.
• Proficient with MongoDB and Redis. Knowledge of Aerospike, other databases would be a bonus.
• Good understanding of distributed systems (servers, databases, etc.).
• Positive and solution-oriented mindset and comfort working in a highly agile, intensely iterative software development environment.