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.

---

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.

---

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

---

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.

---

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.

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

---

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.

---

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.

---

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

---

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.

---

HOW TO APPLY

Send us:

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

Users love Cutshort

Read about what our users have to say about finding their next opportunity on Cutshort.

Shubham Vishwakarma

Full Stack Developer - Averlon

I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.

Companies hiring on Cutshort

About Juliet AI, Inc.

Founded :

2025

Type :

Product

Size :

0-20

Stage :

Bootstrapped

About

www.juliet.space

Agentic AI Coding

Company social profiles

N/A

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Bengaluru (Bangalore)

4 - 6 yrs

₹12L - ₹15L / yr

Python

Django

Python DevOps,
Must have - Strong python

· Must have - Familiarity with RESTful API development (Kafka).

Backend Developer

at Dotball Interactive Private Limited

3 recruiters

Posted by Veena K V

Bengaluru (Bangalore)

1 - 3 yrs

₹3L - ₹8L / yr

NodeJS (Node.js)

Python

PHP

Ruby on Rails (ROR)

NOSQL Databases

+1 more

- Knowledge of Node.js and frameworks such as Express, StrongLoop, etc - Understanding the nature of asynchronous programming and its quirks and workarounds - Good understanding of server-side templating languages like Jade, EJS, etc

Backend Architect

at Powertofly

1 recruiter

Posted by Mrunal Borade

Remote only

5 - 10 yrs

₹15L - ₹27L / yr

Java

Python

NodeJS (Node.js)

Javascript

Amazon Web Services (AWS)

+4 more

Job description

Lead design, development, implementation and maintenance of applications & back-end services demonstrating service-oriented architecture.
Design, build, test, and maintain scalable APIs, services, and systems within the platform.
Choose the right Data Structures, tools, and tech stacks and do high-level design with guidance.
Build, develop, mentor, review code and coach junior team members.
Extensive programming experience with cross-platform development: Java/SpringBoot, Javascript/Node.js, Express.js or Python
Extensive knowledge of ElasticSearch, MongoDB or Cassandra, Redis, SQS and data streaming (Spark, Flink, Kafka streams, storm, etc.).
Well versed in Kafka Understanding cloud native technologies such as Docker and Kubernetes, capable to cover full development lifecycle including CI/CD
Experience in use of source code management system like GIT, bitbucket and build tools like ant, maven, Gradle or make.
Take great pride in Code quality and developer productivity.
Put in Microservcies architecture in place that paves road for scalability, efficiency, observability, and availability.
Build (and open source) data processing, storage and fetch systems at the petabyte scale with the lowest cost/GB while still responding in milliseconds at the 99th percentile.
Write algorithms and services to influence personalisation and recommendation from a real-time recommendation engine for both home feed to surface most viral videos + video e-commerce
Build machine learning pipelines using Kinesis,Spark/Flink/TensorFlow etc
Agile methodologies, Sprint management, Roadmap, Mentoring, Documenting, Software architecture
Proven experience in handling large infrastructure and distributed systems Liaison with Product Management, DevOps, QA, Client and other teams Your Experience Across The Years in the Roles You’ve Played

Requirement:

Have total or more 7 - 9 years of experience with 2-3 years in a startup. Have B.Tech or M.Tech or equivalent academic qualification from premier institute. Experience in Product companies working on Internet-scale applications is preferred
Thoroughly aware of cloud computing infrastructure on AWS leveraging cloud native service and infrastructure services to design solutions.
Follow Cloud Native Computing Foundation leveraging mature open source projects including understanding of containerisation/Kubernetes.

We Value Engineers Who Are :

Customer-focused: We believe that doing what’s right for the creator is ultimately what will drive our business forward.
Obsessed with Quality: Your Production code just works & scales linearly
Team players. You believe that more can be achieved together. You listen to feedback and also provide supportive feedback to help others grow/improve.
Pragmatic: We do things quickly to learn what our creators desire. You know when it’s appropriate to take shortcuts that don’t sacrifice quality or maintainability

Chingari Benefits

The glory. Almost too much responsibility.

A fun-life balance

A ticket on our rocket ship to the moon. ��

Job description

Lead design, development, implementation and maintenance of applications & back-end services demonstrating service-oriented architecture.
Design, build, test, and maintain scalable APIs, services, and systems within the platform.
Choose the right Data Structures, tools, and tech stacks and do high-level design with guidance.
Build, develop, mentor, review code and coach junior team members.
Extensive programming experience with cross-platform development: Java/SpringBoot, Javascript/Node.js, Express.js or Python
Extensive knowledge of ElasticSearch, MongoDB or Cassandra, Redis, SQS and data streaming (Spark, Flink, Kafka streams, storm, etc.).
Well versed in Kafka Understanding cloud native technologies such as Docker and Kubernetes, capable to cover full development lifecycle including CI/CD
Experience in use of source code management system like GIT, bitbucket and build tools like ant, maven, Gradle or make.
Take great pride in Code quality and developer productivity.
Put in Microservcies architecture in place that paves road for scalability, efficiency, observability, and availability.
Build (and open source) data processing, storage and fetch systems at the petabyte scale with the lowest cost/GB while still responding in milliseconds at the 99th percentile.
Write algorithms and services to influence personalisation and recommendation from a real-time recommendation engine for both home feed to surface most viral videos + video e-commerce
Build machine learning pipelines using Kinesis,Spark/Flink/TensorFlow etc
Agile methodologies, Sprint management, Roadmap, Mentoring, Documenting, Software architecture
Proven experience in handling large infrastructure and distributed systems Liaison with Product Management, DevOps, QA, Client and other teams Your Experience Across The Years in the Roles You’ve Played

Requirement:

Have total or more 7 - 9 years of experience with 2-3 years in a startup. Have B.Tech or M.Tech or equivalent academic qualification from premier institute. Experience in Product companies working on Internet-scale applications is preferred
Thoroughly aware of cloud computing infrastructure on AWS leveraging cloud native service and infrastructure services to design solutions.
Follow Cloud Native Computing Foundation leveraging mature open source projects including understanding of containerisation/Kubernetes.

We Value Engineers Who Are :

Customer-focused: We believe that doing what’s right for the creator is ultimately what will drive our business forward.
Obsessed with Quality: Your Production code just works & scales linearly
Team players. You believe that more can be achieved together. You listen to feedback and also provide supportive feedback to help others grow/improve.
Pragmatic: We do things quickly to learn what our creators desire. You know when it’s appropriate to take shortcuts that don’t sacrifice quality or maintainability

Chingari Benefits

The glory. Almost too much responsibility.

A fun-life balance

A ticket on our rocket ship to the moon. ��

Backend Engineer

Fintech Startup in India

Agency job

via Meyrahkee Advisors by Swati Khanna

Bengaluru (Bangalore)

3 - 7 yrs

₹30L - ₹50L / yr

Go Programming (Golang)

Java

Python

You will be a good technical fit at SETU if ● You have architected systems at scale and understand the nuances of building high throughput SaaS platforms. ● You have a strong working knowledge of the language, constructs, and paradigms of either Go— goroutines, dependency management, templating, routing, web frameworks, or Java— Core Java, multi-threading, Spring framework, ORM ● You are adept at entity modeling, query performance tuning, sharding, etc. using PostgreSQL / MySQL / NoSQL databases ● You have experience with Kubernetes / CI/CD / Terraform / Swagger. What you will do at SETU ● Write scalable, robust, automatable, efficient and maintainable code. ● Build frameworks and reusable components. ● Build REST APIs over the financial services infrastructure for developer consumption. ● Help design and architect a scalable, microservices-based platform. ● Solve complex business problems at scale to launch new products and services.