Founding Engineer- Full Stack + AI

Total Experience: 4+ years

Mode of Hire: Permanent

Required Skills Set (Mandatory): HTML, JavaScript, Node.js, Express.js, MongoDB, React/Next.js, AI Integration (LLMs/APIs - OpenAI, Anthropic, Gemini)

Desired Skills (Good if you have): Cloud Platforms (AWS), System Design, Application Security

What is the role all about?

We're hiring full-stack engineers who build with AI, not the traditional way. You should be fluent in modern web engineering, primarily Node.js, and just as fluent in using LLMs and AI tools (Cursor, Claude Code, and similar) to ship fast. Work that once took a month should take a week; what took a week should take a day.

The role spans a range, from architecting backends for non-trivial products like assistants and agents, to rapidly turning a requirement into a clean, customer-facing app or MVP. Be strong in at least one area, be comfortable across the system as a whole, and tell us where you're strongest so we can place you accordingly.

What will you do?

• Plan, build, and ship product features end-to-end, with AI embedded where it has the most impact.
• Integrate LLMs and AI APIs into production-grade applications.
• Use AI tools to prototype, build, and deliver at high speed without sacrificing quality.
• Design scalable APIs and data models with Node.js, Express.js, and MongoDB.
• Build responsive, performant, customer-facing interfaces with React/Next.js.
• Contribute to design discussions, code reviews, and architectural decisions.

What are we looking for?

AI leverage: 

• You've shipped real things using LLMs or AI APIs and instinctively reach for AI to move faster. 
• Comfortable with prompt engineering and judging AI output for production-readiness.

Engineering depth and delivery:

• Solid fundamentals: problem-solving, data structures, and how systems fit together. 
• At least 2+ years across frontend (React/Next.js), APIs (Node.js/Express.js), and databases (MongoDB). 
• You write clean, production-grade code and you ship.
• Knowledge of application security or ethical hacking is an advantage.

Culture

• Work with performance-oriented teams driven by ownership and passion.
• Learn to design systems for high accuracy, efficiency, and scalability.
• No strict deadlines, focus on delivering quality work.
• Meritocracy-driven, candid culture. No politics.
• Very high visibility regarding which startups and markets are exciting globally.

About Tracxn

Tracxn (Tracxn.com) is a Bangalore-based product company that provides a research and deal-sourcing platform for Venture Capital, Private Equity, Corp Dev, and professionals in the startup ecosystem.

We are a team of 800+ working professionals serving customers across the globe. Our clients include Funds such as Andreessen Horowitz, Matrix Partners, and GGV Capital, as well as Large Corporates such as Citi, Embraer & Ferrero.

Founders

• Neha Singh (ex-Sequoia, BCG | MBA - Stanford GSB)
• Abhishek Goyal (ex-Accel Partners, Amazon | BTech - IIT Kanpur)

About Technology Team

Tracxn's Technology team is 50+ members strong and growing. The technology team is subdivided into multiple smaller teams, each of which owns one or more services/components of the technology platform. Ours is a young team of motivated engineers with a minimal management structure, in which almost everyone is actively involved in technical development and design. We have a team-centric culture where ownership and responsibility for a feature or module lie with a team rather than an individual.

We work on an array of technologies, including but not limited to ReactJS, Next.js, Storybook, Webpack, Node, Mongo, AWS Lambda, Spring, Elastic Stack, MySQL, Kafka, Redis, Ansible, etc.

We value ownership, continuous learning, consistency, and discipline as a team.

Total Experience: 4+ years

Mode of Hire: Permanent

Required Skills Set (Mandatory): HTML, JavaScript, Node.js, Express.js, MongoDB, React/Next.js, AI Integration (LLMs/APIs - OpenAI, Anthropic, Gemini)

Desired Skills (Good if you have): Cloud Platforms (AWS), System Design, Application Security

What is the role all about?

We're hiring full-stack engineers who build with AI, not the traditional way. You should be fluent in modern web engineering, primarily Node.js, and just as fluent in using LLMs and AI tools (Cursor, Claude Code, and similar) to ship fast. Work that once took a month should take a week; what took a week should take a day.

The role spans a range, from architecting backends for non-trivial products like assistants and agents, to rapidly turning a requirement into a clean, customer-facing app or MVP. Be strong in at least one area, be comfortable across the system as a whole, and tell us where you're strongest so we can place you accordingly.

What will you do?

• Plan, build, and ship product features end-to-end, with AI embedded where it has the most impact.
• Integrate LLMs and AI APIs into production-grade applications.
• Use AI tools to prototype, build, and deliver at high speed without sacrificing quality.
• Design scalable APIs and data models with Node.js, Express.js, and MongoDB.
• Build responsive, performant, customer-facing interfaces with React/Next.js.
• Contribute to design discussions, code reviews, and architectural decisions.

What are we looking for?

AI leverage: 

• You've shipped real things using LLMs or AI APIs and instinctively reach for AI to move faster. 
• Comfortable with prompt engineering and judging AI output for production-readiness.

Engineering depth and delivery:

• Solid fundamentals: problem-solving, data structures, and how systems fit together. 
• At least 2+ years across frontend (React/Next.js), APIs (Node.js/Express.js), and databases (MongoDB). 
• You write clean, production-grade code and you ship.
• Knowledge of application security or ethical hacking is an advantage.

Culture

• Work with performance-oriented teams driven by ownership and passion.
• Learn to design systems for high accuracy, efficiency, and scalability.
• No strict deadlines, focus on delivering quality work.
• Meritocracy-driven, candid culture. No politics.
• Very high visibility regarding which startups and markets are exciting globally.

About Tracxn

Tracxn (Tracxn.com) is a Bangalore-based product company that provides a research and deal-sourcing platform for Venture Capital, Private Equity, Corp Dev, and professionals in the startup ecosystem.

We are a team of 800+ working professionals serving customers across the globe. Our clients include Funds such as Andreessen Horowitz, Matrix Partners, and GGV Capital, as well as Large Corporates such as Citi, Embraer & Ferrero.

Founders

• Neha Singh (ex-Sequoia, BCG | MBA - Stanford GSB)
• Abhishek Goyal (ex-Accel Partners, Amazon | BTech - IIT Kanpur)

About Technology Team

Tracxn's Technology team is 50+ members strong and growing. The technology team is subdivided into multiple smaller teams, each of which owns one or more services/components of the technology platform. Ours is a young team of motivated engineers with a minimal management structure, in which almost everyone is actively involved in technical development and design. We have a team-centric culture where ownership and responsibility for a feature or module lie with a team rather than an individual.

We work on an array of technologies, including but not limited to ReactJS, Next.js, Storybook, Webpack, Node, Mongo, AWS Lambda, Spring, Elastic Stack, MySQL, Kafka, Redis, Ansible, etc.

We value ownership, continuous learning, consistency, and discipline as a team.

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.

Responsibilities Include:

● Architecting, building, testing, and deploying applications that support our transportation network

● Modifying designs and specifications of complex applications

● Collaborating and adding value through participation in peer code reviews, providing comments and suggestions

● Leverage AWS and other cloud technologies to design and implement systems in a serverless and event-driven environment

● Working with technical and non-technical end-users, other engineers, and product managers in a cross-functional, quick-moving, and collaborative environment

● Analyzing code, requirements, system risks, and software reliability and providing recommendations on how to leverage our technology more efficiently

● Working with Product and Design to confirm requirements, prioritization, and development of new features

● Design and implement LLM-powered features to solve complex logistics challenges, automate manual operational workflows, and unlock new efficiencies for our network.

● Champion AI-assisted engineering practices by integrating machine learning and intelligent automation into our CI/CD pipelines to predict deployment risks and accelerate delivery cycles.

What You Bring:

● Ability to adapt to changing requirements and work in a fast-paced environment.

● Ability to work effectively in a cross-functional team environment.

● 7+ years of experience building, testing and deploying applications in high-traffic production environments

● 7+ years of experience developing software with Javascript, Node.js and React

● Enjoys taking initiative, is a self-starter, willing to move fast and ship quick, and is excited about collaborating on big challenges

Preferred Qualifications:

● Experience in transportation, logistics or network orchestration systems is highly desirable

● Experience working in a remote first environment.

● Proficiency with AWS, GCP, or similar cloud platforms.

● Strong skills in React and Node.js for end-to-end development. 

About LeadSquared

LeadSquared is a leading sales execution and marketing automation platform trusted by 2,000+ businesses globally, including healthcare, education, financial services, and real estate. Headquartered in Bengaluru with offices across the US, UK, UAE, and Southeast Asia, we empower sales teams to close faster, smarter, and at scale.

Our AI team is at the forefront of integrating cutting-edge large language model capabilities into enterprise workflows — building intelligent agents, copilots, and automation systems that redefine how businesses operate.

Role Overview

We are looking for a Senior AI Engineer with hands-on experience building LLM-powered agents and agentic AI systems. You will design, develop, and deploy autonomous AI pipelines that solve complex, multi-step business problems — from lead qualification and follow-up automation to intelligent CRM workflows and beyond.

This role is ideal for someone who is deeply excited about the frontier of AI, can move fast, and wants their work to directly impact millions of sales professionals worldwide.

Key Responsibilities

•

Design and build LLM-powered agentic systems using frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI to automate complex, multi-step workflows.

•

Develop and maintain Retrieval-Augmented Generation (RAG) pipelines with vector databases (Pinecone, Weaviate, Chroma, pgvector) for domain-specific knowledge grounding.

•

Build and integrate tool-use and function-calling capabilities into AI agents, enabling dynamic interaction with internal APIs, databases, and third-party services.

•

Implement prompt engineering strategies including chain-of-thought, few-shot prompting, and structured output parsing to ensure reliable agent behavior.

•

Design evaluation frameworks and observability pipelines (LangSmith, Helicone, custom metrics) to monitor agent performance, accuracy, and cost.

•

Collaborate with product, sales, and domain teams to translate business requirements into AI-driven solutions and features.

•

Optimize LLM inference for latency and cost using techniques like caching, model distillation, quantization, and batching.

•

Stay current with the rapidly evolving LLM ecosystem and proactively propose improvements and new approaches.

•

Contribute to internal best practices, documentation, and knowledge-sharing across the engineering org.

Required Qualifications

Experience

•

2–4 years of professional software engineering experience, with at least 1–2 years focused on LLM/AI systems.

•

Proven experience shipping LLM-based products or agentic AI systems into production environments.

Technical Skills

•

Strong proficiency in Python and familiarity with async programming patterns for AI pipelines.

•

Hands-on experience with LLM APIs: OpenAI (GPT-4o), Anthropic (Claude), Google (Gemini), or open-source models (Llama, Mistral).

•

Experience with agentic frameworks: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar.

•

Solid understanding of RAG architectures, embedding models, and semantic search.

•

Experience with vector databases and similarity search infrastructure.

•

Knowledge of REST APIs, microservices architecture, and containerization (Docker/Kubernetes).

Problem-Solving & Mindset

•

Strong ability to decompose ambiguous, open-ended problems into structured AI system designs.

•

Experience with prompt debugging, LLM evaluation, and iterative refinement workflows.

•

Ability to balance research exploration with engineering pragmatism to ship reliable systems.

Preferred Qualifications

•

Experience with multi-agent orchestration and agent memory systems (short-term and long-term).

•

Familiarity with fine-tuning or RLHF workflows for domain adaptation.

•

Background in NLP, information retrieval, or conversational AI.

•

Prior experience in B2B SaaS or CRM domain is a plus.

•

Contributions to open-source AI/ML projects or published research/blogs.

•

Experience with cloud platforms: AWS, GCP, or Azure — particularly AI/ML services

Location: Jaipur (Work From Office)

Employment Type: Full-Time

We're looking for a GenAI Engineer (LLM Engineer) to build scalable AI-powered SaaS applications using Large Language Models (LLMs). You'll develop intelligent AI workflows, integrate LLMs into production systems, and build secure, high-performance AI solutions.

Key Responsibilities

• Integrate LLM APIs (OpenAI, Claude, Hugging Face) into production applications.
• Design and optimize RAG pipelines and prompt engineering workflows.
• Build and manage Vector Databases (Pinecone, Weaviate, pgvector).
• Optimize AI performance, latency, and operational cost.
• Ensure secure, scalable AI architecture.
• Collaborate with Product and Engineering teams to deliver AI-powered features.

Requirements

• 3+ years of backend development using Python, Go, or Node.js.
• Hands-on experience with LLMs, LangChain or LlamaIndex.
• Strong understanding of RAG, Prompt Engineering, and Vector Databases.
• Experience with AWS, GCP, or Azure.
• Knowledge of APIs, Microservices, and AI application development.

Preferred: Experience in SaaS/FinTech, LLMOps, or Model Fine-tuning.

Education: B.Tech, BCA, or equivalent technical qualification.

Apply Now

Application Form: https://zfrmz.com/pAKb2ynfomIsuNwRfRbV?utm_source=cutshort

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams

About the Role

SwitchKart is on a mission to make technology more accessible and more sustainable — we're in the business of recommerce, giving old smartphones a second life, cutting down e-waste, and extending the lifecycle of every device we touch.

We're looking for a Senior Full Stack Developer to help us build and scale the ecosystem of platforms powering this mission — from our procurement app to our retailer app, pricing engines, and warranty systems. You'll take ownership of complex features end-to-end, mentor junior engineers, and make architectural decisions that shape how we grow.

What You'll Do

• Own Features End-to-End: Design, build, and ship full stack features across our procurement, retailer, pricing, and warranty platforms — from database schema to UI polish.

• Drive Architecture: Make key technical decisions on system design, scalability, and code structure as our ecosystem of apps grows.

• Build AI-First: Design and build systems with AI at the core — not bolted on. Think about where AI can automate, assist, or enhance the products you're building from day one.

• Build Scalable Architecture: Build and monitor a highly performant, failure-resistant platform — we take pride in doing this with a small, high-ownership team.

• Automate and Integrate: Develop tools that automate our integration processes and build data pipelines across our app ecosystem.

• Foster Technical Excellence: Champion unit and integration testing and lead meaningful code reviews across the team.

• Prototype and Validate: Create interactive prototypes to prove out technical concepts and participate in pilots for new initiatives.

• Mentor the Team: Guide junior developers through code reviews, pairing, and technical direction.

• Report Upward: Provide regular updates to management on milestones, risks, issues, and mitigation plans.

• Collaborate Cross-Functionally: Work closely with product and design to translate requirements into robust technical solutions across multiple products.

What We're Looking For

Must Have

• 4+ years of full stack development experience

• Strong proficiency in React and Node.js

• Solid experience with PostgreSQL or MySQL — schema design, query optimisation

• Experience designing and scaling production systems

• Experience deploying and managing applications on a cloud platform (AWS/GCP or similar)

• Comfortable owning a feature from concept to deployment

• Strong debugging and problem-solving skills

Good to Have

• Experience mentoring or leading junior engineers

• Track record of driving scalability and time-to-market in past cloud architecture decisions

• Exposure to CI/CD pipelines

• Experience with Docker, NoSQL databases, or distributed caching

• Experience integrating third-party REST/SOAP APIs

• Experience in a fast-moving startup environment

Why SwitchKart

• Real ownership over architecture and technical direction.

• Access to the latest AI coding agents and tools — we invest in keeping our engineers on the cutting edge.

• Work on a genuinely differentiated business with measurable impact.

• Be part of a lean team where your decisions shape the product.

• Opportunity to mentor and grow the engineering team.

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.

Role: Full Stack JavaScript/TypeScript Developer

We're looking for a Full Stack Developer with strong JavaScript/TypeScript fundamentals to join our team and help build AI-powered product features.

Responsibilities:

Core Skills & Competencies (Must have):

• Strong proficiency in TypeScript and solid JavaScript fundamentals
• Front-end development skills with the React ecosystem (Next.js), including state management libraries like Zustand, Redux
• Expertise in HTML/CSS, with experience creating responsive and adaptive designs
• Experience building AI-assisted features such as chatbots, content generation, semantic search, recommendations, or intelligent automation
• Experience with RESTful services and APIs
• Familiarity with AI SDKs, LLM APIs, and vector databases
• Experience with SQL and database management, understanding relational databases, and ability to write efficient and optimized queries
• Understanding of database design and management, especially with SQL
• Experience with version control systems such as Git
• 
  

Desired Skills & Competencies (Nice to have):

• Experience with event-driven architecture
• Experience with cloud services like Azure or AWS
• Familiarity with modern DevOps practices
• Understanding of security practices and web application security
• Familiarity with CI/CD pipelines
• 
  

What we're looking for:

• Strong command over JS/TS fundamentals, not just framework-level knowledge
• Candidates with internship experience or a background from a reputed engineering college preferred
• Please share your GitHub link, portfolio, or details of projects you've built (personal, academic, or professional)