AI-Full Stack Developer

Job Title : Senior Consultant – Full Stack Developer with AI

Experience : 5+ Years

Open Positions : 1

Location : Remote

Working Hours : 11:00 AM to 08:00 PM IST

Engagement : 6 to 8 Months Contract-to-Hire (C2H), with potential conversion to client payroll

Expected Joining : By the last week of August / 1st week of September

Role Overview :

Thoughtworks is looking for a Senior Consultant – Full Stack Developer with AI experience who can design and develop scalable full-stack applications while leveraging modern AI development tools and agentic AI capabilities.

The ideal candidate should have strong hands-on experience with Python, JavaScript / React.js, AWS Bedrock Agent Core, Docker, Kubernetes, and modern AI-assisted development frameworks and tools. Experience building MCP servers / tools, AI skills, or integrations using tools such as Cursor, Claude Code, Codex, or GitHub Copilot will be highly valuable.

The candidate should be comfortable working across application development, AI integration, cloud technologies, and containerized environments.

Mandatory Skills :

Python, React.js / JavaScript, AWS Bedrock Agent Core, Docker, Kubernetes, MCP / AI Skills, Cursor / Claude Code / Codex / GitHub Copilot, Full-Stack Development.

Key Responsibilities :

• Design, develop, and maintain scalable full-stack applications using modern development practices.
• Build backend services and APIs using Python and related frameworks.
• Develop responsive and scalable frontend applications using ReactJS or other JavaScript frameworks.
• Design and implement AI-powered solutions using AWS Bedrock Agent Core.
• Build and integrate AI agents, tools, skills, and workflows into enterprise applications.
• Develop and work with MCP (Model Context Protocol) servers, tools, or integrations.
• Leverage AI-assisted development platforms and coding tools such as Cursor, Claude Code, Codex, or GitHub Copilot.
• Containerize applications and services using Docker.
• Deploy, manage, and troubleshoot containerized workloads using Kubernetes.
• Collaborate with cross-functional teams to understand business requirements and translate them into scalable technical solutions.
• Follow engineering best practices around code quality, testing, security, performance, and maintainability.
• Contribute to CI/CD and cloud deployment processes; DevOps experience will be an added advantage.
• Participate in technical discussions, architecture decisions, code reviews, and project delivery.

Mandatory Skills :

• 5+ years of relevant software development experience.
• Strong hands-on experience with Python.
• Strong experience with ReactJS or another modern JavaScript framework.
• Hands-on experience with AWS Bedrock Agent Core.
• Strong experience with Docker.
• Hands-on experience with Kubernetes.
• Experience building MCP servers / tools, AI skills, or similar AI integrations.
• Experience using AI-assisted coding/development tools such as :
• Cursor
• Claude Code
• Codex
• GitHub Copilot
• Strong understanding of full-stack application development.
• Good understanding of API development, application architecture, and cloud-based solutions.

Nice to Have :

• Experience with DevOps practices and CI/CD pipelines.
• Experience with AWS cloud services beyond Bedrock.
• Experience with infrastructure automation and deployment.
• Experience building production-grade GenAI / Agentic AI applications.
• Experience with LLM integrations, AI agents, tools, and function calling.

Project Expectations :

Candidates should be able to explain at least one recent project in detail, including :

• Problem Statement : What business / technical problem were you solving ?
• Architecture & Approach : How did you design the solution ?
• Key Contributions : What did you personally build or own ?
• AI / Agent Implementation : How did you use AWS Bedrock Agent Core, MCP, or AI development tools ?
• Technology Stack : Python, React.js / JavaScript, AWS, Docker, Kubernetes, etc.
• Challenges : What were the major technical challenges ?
• Outcomes & Metrics : What measurable impact did the solution deliver, such as performance improvement, cost reduction, automation, productivity improvement, or reduced development time ?

Interview Process :

1. Round 1 – GT Technical Interview : 60 minutes
2. Round 2 – Client Technical Interview : 60 minutes
3. Round 3 – Project Round : 60 minutes
4. Additional Client Round : May be conducted on a case-by-case basis

Key Hiring Priorities :

Highest priority : Candidates with genuine hands-on experience in AWS Bedrock Agent Core + Python + React / JavaScript + Docker + Kubernetes + MCP / AI skills and practical experience using modern AI coding/agent development tools.

Note : Candidates should demonstrate hands-on implementation experience rather than only theoretical knowledge or exposure to the above technologies.

We are building an advanced, AI-driven multi-agent software system designed to revolutionize task automation and code generation. This is a futuristic AI platform capable of:

✅ Real-time self-coding based on tasks  

✅ Autonomous multi-agent collaboration  

✅ AI-powered decision-making  

✅ Cross-platform compatibility (Desktop, Web, Mobile)  

We are hiring a highly skilled **AI Engineer & Full-Stack Developer** based in India, with a strong background in AI/ML, multi-agent architecture, and scalable, production-grade software development.

### Responsibilities:

- Build and maintain a multi-agent AI system (AutoGPT, BabyAGI, MetaGPT concepts)  

- Integrate large language models (GPT-4o, Claude, open-source LLMs)  

- Develop full-stack components (Backend: Python, FastAPI/Flask, Frontend: React/Next.js)  

- Work on real-time task execution pipelines  

- Build cross-platform apps using Electron or Flutter  

- Implement Redis, Vector databases, scalable APIs  

- Guide the architecture of autonomous, self-coding AI systems  

### Must-Have Skills:

- Python (advanced, AI applications)  

- AI/ML experience, including multi-agent orchestration  

- LLM integration knowledge  

- Full-stack development: React or Next.js  

- Redis, Vector Databases (e.g., Pinecone, FAISS)  

- Real-time applications (websockets, event-driven)  

- Cloud deployment (AWS, GCP)  

### Good to Have:

- Experience with code-generation AI models (Codex, GPT-4o coding abilities)  

- Microservices and secure system design  

- Knowledge of AI for workflow automation and productivity tools  

Join us to work on cutting-edge AI technology that builds the future of autonomous software.

Job Description

We are looking for an experienced Python Full Stack – GenAI / Agentic AI Engineer with 7+ years of experience in software development and strong hands-on expertise in Python backend development, React JS, Generative AI, and Agentic AI.

The ideal candidate should have experience building scalable backend services, modern web applications, and AI-powered applications using LLMs, RAG, agentic frameworks, and cloud platforms.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python.
• Develop robust REST APIs and microservices using FastAPI, Flask, or Django.
• Design API architecture, authentication mechanisms, error handling, and integrations.
• Develop responsive and interactive frontend applications using React JS.
• Work with React components, hooks, state management, and API integrations.
• Build and integrate Generative AI and Agentic AI applications using LLMs.
• Develop AI agents using frameworks such as LangChain and LangGraph.
• Implement RAG, embeddings, vector search, tool calling, memory, planning, and reasoning.
• Design and implement multi-agent systems and AI workflows.
• Apply prompt engineering techniques and appropriate guardrails for AI applications.
• Integrate AI applications with cloud-based AI platforms and services.
• Deploy applications using containers and cloud platforms.
• Work with CI/CD pipelines and application monitoring.
• Collaborate with cross-functional teams to design and deliver scalable solutions.

Required Skills

• 7+ years of overall software development experience.
• Strong hands-on experience in Python.
• Strong experience with FastAPI and REST API development.
• Experience with microservices architecture and API design.
• Hands-on experience with React JS.
• Strong experience in Generative AI / LLM applications.
• Hands-on experience in Agentic AI development.
• Experience with LangChain / LangGraph.
• Strong understanding of RAG, embeddings, vector search, and tool calling.
• Experience with multi-agent systems, memory, planning, and reasoning.
• Experience with at least one major cloud platform – AWS / Azure / GCP.
• Experience with containers, CI/CD, deployment, and monitoring.

Preferred Skills

• Google ADK
• Semantic Kernel
• Azure OpenAI
• Vertex AI
• AWS Bedrock
• Docker / Kubernetes
• AI application monitoring and observability
• Frontend testing and application performance optimization

Opportunity Details

Role: Python Full Stack – GenAI / Agentic AI Engineer

Experience: 7+ Years

Location: Hyderabad

Employment: Permanent Position

Work Mode: As per client requirement

Mandate Skills: Python, FastAPI, React JS, Agentic AI, LangChain/LangGraph, RAG, LLM, Cloud

Interview Focus Areas

Candidates should be prepared to demonstrate practical experience in:

• Python backend development
• FastAPI and REST APIs
• Microservices and API design
• React JS
• LLM / Generative AI applications
• Agentic AI architecture
• LangChain / LangGraph
• RAG and vector search
• Tool calling and multi-agent systems
• Cloud deployment and CI/CD

Role Overview

We are looking for a skilled Python Full Stack / Agentic AI Engineer to design, develop, and deploy AI-powered applications and intelligent agentic workflows. The ideal candidate should have strong expertise in Python, FastAPI, LLMs, RAG, LangChain/LangGraph, and modern full-stack development.

You will work on building scalable backend services, integrating Large Language Models, developing AI agents, implementing Retrieval-Augmented Generation (RAG) pipelines, and creating production-ready AI applications.

Key Responsibilities

• Design and develop scalable backend applications using Python and FastAPI.
• Build and deploy Agentic AI solutions using LLMs and agent frameworks.
• Develop multi-step and multi-agent workflows using LangChain and LangGraph.
• Design and implement RAG (Retrieval-Augmented Generation) pipelines.
• Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models.
• Develop prompt engineering strategies and structured LLM workflows.
• Work with vector databases and embedding models for semantic search and knowledge retrieval.
• Build APIs and microservices for AI-powered applications.
• Integrate AI services with databases, third-party APIs, and enterprise systems.
• Develop conversation memory, tool calling, function calling, and agent orchestration capabilities.
• Implement evaluation, monitoring, logging, guardrails, and error handling for AI applications.
• Optimize applications for performance, scalability, reliability, and cost.
• Collaborate with product managers, frontend developers, data engineers, and other stakeholders.
• Write clean, maintainable, well-tested, and production-ready code.
• Participate in architecture discussions, code reviews, testing, and deployment activities.

Required Skills

Programming & Backend

• Strong proficiency in Python.
• Hands-on experience with FastAPI, REST APIs, and backend development.
• Strong understanding of asynchronous programming, API design, authentication, and middleware.
• Experience with SQL/NoSQL databases.

Generative AI / Agentic AI

• Strong understanding of LLMs and Generative AI.
• Hands-on experience building AI Agents / Agentic AI applications.
• Experience with LangChain and/or LangGraph.
• Knowledge of agent orchestration, tool calling, function calling, memory, and workflow management.
• Strong understanding of prompt engineering.

RAG

• Experience designing and implementing RAG architectures.
• Knowledge of document ingestion, chunking, embeddings, vector search, retrieval, reranking, and response generation.
• Experience with vector databases such as FAISS, Chroma, Pinecone, Weaviate, Qdrant, or similar.

LLM & AI Integration

• Experience integrating commercial or open-source LLMs.
• Understanding of embeddings, context windows, temperature, token usage, and model selection.
• Experience with structured outputs and LLM-based workflows.
• Familiarity with LLM evaluation and observability is a plus.

Full Stack

• Working knowledge of HTML, CSS, JavaScript/TypeScript.
• Experience with React.js or similar frontend frameworks is preferred.
• Ability to integrate frontend applications with Python/FastAPI services.

Position Overview

We are seeking a versatile Senior Full Stack & AI Agent Developer to architect, build, and

maintain end-to-end software solutions spanning web platforms, desktop applications, and

autonomous AI agents capable of interacting with and controlling these software systems.

The ideal candidate will bridge traditional engineering software with cutting-edge artificial

intelligence to automate data processing and enhance operational decision-making. While

not strictly required, a background or strong interest in the energy sector—specifically

drilling and completion operations—is highly desirable.

Key Responsibilities

• Full Stack Development: Design, develop, and deploy robust web applications and

native desktop software utilized by engineering and operational teams.

• AI Agent Engineering: Build, train, and integrate autonomous AI agents and LLM-

driven workflows capable of interpreting data, executing commands, and safely

controlling desktop and web-based software.

• Workflow Automation: Translate complex workflows into intuitive software features

and autonomous agent actions, minimizing manual data entry and operational

bottlenecks.

• Data Integration: Handle high-frequency data streams and integrate them seamlessly

into user interfaces and backend AI models.

• Architecture & Scalability: Ensure high performance, security, and scalability across

cloud infrastructure (AWS/Azure), local desktop environments, and potential edge

computing setups.

• Cross-Functional Collaboration: Work closely with domain experts and end-users to

translate field challenges into technical product requirements.

Required Qualifications & Experience

• Experience: Minimum of 5 years of professional software development experience,

with a proven track record of delivering production-ready web and desktop

applications.

• Programming Languages: Strong proficiency in Python, JavaScript/TypeScript, and at

least one compiled language (C#, C++, or Java).• Web & Desktop Frameworks: Hands-on experience with modern frontend

frameworks (React, Angular, or Vue.js), Node.js, and desktop application development

(Electron, WPF, Qt, or Tauri).

• AI & Agent Tooling: Demonstrated experience building AI agents using LLM APIs

(OpenAI, Anthropic), open-source models (Hugging Face), LangChain, LlamaIndex,

AutoGPT, or custom agent architectures.

• Automation & UI Control: Expertise in software control mechanisms using tools like

Selenium, Playwright, PyAutoGUI, Appium, or computer vision-based GUI automation to

allow AI agents to navigate software.

• Cloud, DevOps & Databases: Experience with Git, Docker, CI/CD pipelines, cloud

platforms (AWS/Azure/GCP), RESTful APIs, GraphQL, and relational/NoSQL databases.

Preferred Qualifications (Strong Plus)

• Industry Domain Expertise: Prior hands-on development experience within the oil and

gas sector, specifically focused on drilling, completions, rig operations, or subsurface

engineering software.

• Data & Protocols: Familiarity with oilfield data standards (e.g., WITSML, OPC-UA) and

time-series databases.

• Experience deploying AI models and agents in edge or low-connectivity environments

(such as offshore rigs or remote drilling sites).

• Familiarity with safety-critical software design and cybersecurity standards in

industrial control systems (ICS/SCADA).

• Degree in Computer Science, Software Engineering, Petroleum Engineering, or a related technical discipline.

Full Stack Developer

Experience: 3 to 5 Years

Location: Hyderabad

Interview Mode: Face-to-Face (F2F)

Work Mode: Hybrid

Employment Type: Full-Time

Note: Immediate joiners or candidates with a notice period of up to 15 days are preferred. We are only considering candidates who can attend a face-to-face interview at our office.

Role Summary;

We are looking for a Full Stack Developer (React.js + Python + AWS + AI) to design, develop, and maintain scalable web applications and AI-powered solutions. The ideal candidate must have strong experience in React.js, Python, AWS, and AI development. Hands-on AI development experience is mandatory for this role.

Mandatory AI Skill Requirement - AI development experience is mandatory. Candidates without hands-on AI development experience will not be considered.

Candidates must have practical experience in one or more of the following:

• Building AI-powered applications.
• Working with Large Language Models (LLMs).
• Prompt Engineering.
• Retrieval-Augmented Generation (RAG).
• AI agent development using LangChain, LangGraph, or similar frameworks.
• Integrating AI models through APIs such as OpenAI, Anthropic, or Gemini.
• Developing AI-enabled workflows and intelligent business applications.

Note: Experience using AI coding assistants (ChatGPT, GitHub Copilot, Claude, Gemini, etc.) alone does not meet this requirement. Candidates must have actual AI application development experience.

Key Responsibilities

• Develop and maintain full-stack web applications.
• Build responsive frontend applications using React.js.
• Develop backend REST APIs using Python (FastAPI / Django / Flask).
• Design, develop, and integrate AI-powered features into applications.
• Develop and deploy applications on AWS cloud services.
• Work with relational databases (MySQL / PostgreSQL / SQL Server).
• Integrate frontend and backend components.
• Follow Agile/Scrum development processes.
• Write clean, maintainable, and production-ready code.
• Collaborate with cross-functional teams to deliver scalable and high-quality solutions.

Required Skills (Mandatory)

• 3 to 5 years of Full Stack development experience.
• Strong experience in React.js.
• Strong backend development experience in Python.
• Hands-on experience with AWS cloud services.
• Hands-on AI development experience (Mandatory).
• Experience with LLMs, Prompt Engineering, RAG, LangChain, LangGraph, or similar AI frameworks.
• REST API development experience.
• Strong SQL database experience.
• Git and Agile development workflow.
• Good understanding of software design principles and best practices.

Good to Have

• Docker
• CI/CD pipelines
• Microservices architecture
• Kubernetes
• Experience with vector databases and AI model integrations

Preferred Qualifications

• Bachelor's degree in Computer Science or a related field.
• Strong problem-solving and analytical skills.
• Good communication and teamwork abilities.
• Passion for learning new technologies, especially AI, cloud technologies, and modern software development.

Job Title

Python Full Stack Developer – AI

Experience: 6-9 Years

Location: Bangalore (Hybrid)

Employment Type: Full-Time

Job Summary

We are seeking a highly skilled Python Full Stack Developer with AI expertise to design, develop, and deploy scalable AI-powered applications. The ideal candidate should have strong experience in Python, Full Stack Development, REST APIs, modern frontend frameworks, and Generative AI technologies, including LLMs, prompt engineering, and AI integrations.

The role involves building end-to-end web applications, integrating AI models, and collaborating with cross-functional teams to deliver innovative AI-driven solutions.

Key Responsibilities

· Design, develop, and maintain scalable full-stack applications using Python.

· Build responsive and interactive user interfaces using React.js, Angular, or Vue.js.

· Develop backend services and RESTful APIs using Django, Flask, or FastAPI.

· Integrate Generative AI models such as OpenAI GPT, Claude, Gemini, or Llama into business applications.

· Develop AI-powered chatbots, assistants, document processing, and workflow automation solutions.

· Implement prompt engineering techniques to optimize AI model performance.

· Build Retrieval-Augmented Generation (RAG) pipelines using vector databases.

· Work with LangChain, LangGraph, or LlamaIndex for LLM orchestration.

· Integrate AI APIs and third-party services into enterprise applications.

· Design and optimize SQL and NoSQL databases.

· Deploy applications on AWS, Azure, or GCP.

· Develop CI/CD pipelines and manage deployments using Docker and Kubernetes.

· Write clean, reusable, and well-documented code following best practices.

· Participate in Agile ceremonies, code reviews, and sprint planning.

Required Technical Skills

Backend

· Python

· Django

· Flask

· FastAPI

Frontend

· React.js / Angular / Vue.js

· HTML5

· CSS3

· JavaScript (ES6+)

· TypeScript

AI / Generative AI

· OpenAI API

· Azure OpenAI

· Gemini API

· Claude API

· Llama Models

· LangChain

Databases

· PostgreSQL

· MySQL

· MongoDB

· Redis

Cloud & DevOps

· AWS / Azure / Google Cloud Platform

· Docker

· Kubernetes

· Git

· GitHub

· Jenkins

· CI/CD

API Development

· REST APIs

· GraphQL (Preferred)

· API Integration

Preferred Skills

· Machine Learning fundamentals

· NLP (Natural Language Processing)

· Hugging Face Transformers

· TensorFlow or PyTorch

· Kafka or RabbitMQ

· Elasticsearch

· Microservices Architecture

· Authentication (OAuth2, JWT)

Qualifications

· Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

· 6–9 years of experience in Python Full Stack Development.

· Hands-on experience with Generative AI and LLM-based application development.

· Experience working in Agile/Scrum environments. 

Apply: https://processity.ai/careers/fullstack-ai-engineer

BigMantra is a Vertical Autonomous AI Agent Builder — we build AI companies that go a mile deep into specific industries. Our products include Mantra Spaces (AI-powered UK HMO property management) and Verity Law (AI-powered legal conveyancing). Our team is small, our stack is modern, and your code ships to production the same week you write it.

We're looking for a Fullstack AI Applied Engineer who can build full applications end-to-end and wire AI agents into production systems that real users depend on.

WHAT YOU'LL DO

• Build and ship full-stack web applications using React / Next.js and Python / Node.js

• Design and implement AI agent workflows using LangChain, LangGraph, Claude Agent SDK, Agno, or similar

• Integrate agents with real-world APIs — Salesforce, Google Workspace, WhatsApp Business, email providers

• Build and optimize database layers — production SQL, schema design, RAG pipelines

• Own deployment and infrastructure — Docker services, CI/CD pipelines on AWS or Azure

• Write tests that matter — E2E, load tests, performance benchmarks

• Collaborate directly with the founding team on architecture and product direction

MUST HAVE

• 3+ years of professional software engineering experience

• Strong JavaScript / TypeScript — React, Next.js, Node.js in production

• Strong Python — backends, agent systems, data pipelines

• Hands-on experience with at least one AI agent framework (LangChain, LangGraph, Claude Agent SDK, Agno, or equivalent)

• Docker services for containerization and deployment

• CI/CD pipelines — GitHub Actions, GitLab CI, or similar

• Deployment experience on AWS or Azure

• Solid SQL and database skills — schema design, query optimization

GOOD TO HAVE

• Experience with autonomous agents — MCP (Model Context Protocol), skills, plugins, tool-use

• Memory and context management for long-running agents

• Prompt engineering and optimization

COMPENSATION & BENEFITS

• ₹30L – 50L per annum (based on experience)

• Equity / ESOPs — early-stage participation

• Remote-friendly — Coimbatore office available

• Learning budget — courses, conferences, AI tooling subscriptions

• Flexible hours — output over seat time

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:

 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.

About the Role

We are looking for a hands-on Applied AI / Full Stack Engineer to build AI-powered products and experiences. The ideal candidate should be comfortable working across AI, backend, and frontend and taking features from idea to production.

Key Responsibilities

• Build and deploy AI/LLM-powered applications and features.
• Develop AI agents, RAG pipelines, tool/function-calling workflows and integrations.
• Build scalable backend APIs and services.
• Develop frontend applications using React/Next.js.
• Integrate LLMs such as OpenAI, Claude, Gemini, etc.
• Work with databases, cloud platforms and production deployments.
• Collaborate with product and design teams and take ownership of features end-to-end.

Must-Have Skills

• 3–6 years of software engineering experience.
• Strong Python and/or TypeScript/Node.js.
• Strong React.js / Next.js / TypeScript experience.
• Hands-on experience with LLMs / Generative AI.
• Experience with RAG, AI Agents or tool/function calling.
• Experience building and deploying real-world products.
• Good understanding of APIs, databases and cloud deployment.

Good to Have

• LangChain / LangGraph / LlamaIndex
• PostgreSQL / Vector Databases
• AWS / GCP / Azure / Vercel
• Docker / CI/CD
• Experience in an early-stage startup or AI product company.

We are looking for builders who can take a problem, experiment, build, ship and improve it—not just candidates with AI keywords on their resume.