Bold Business - Python Developer - AI Automation & Full Stack

• A disciplined Python and JavaScript developer with the hunger to grow into AI. You don't need to have it all figured out — but you need real fundamentals, shipped work you can speak to, strong English communication skills, and a genuine curiosity about where AI is taking software development. We'll invest in the right person. • English Communication — Must-Have • Advanced to fluent English — written and spoken; this is non-negotiable for an offshore hire • Ability to explain technical concepts clearly to non-technical stakeholders (clients, PMs, business owners) • Professional written communication: emails, Slack messages, documentation, and status updates must be clear and polished • Comfort on video calls and async communication with a U.S.-based team • 2–4 years of hands-on development — CS degree, bootcamp, or self-taught with shipped projects and a GitHub that shows it • Python (Required) — demonstrated in real work: automation, scripting, backend logic, or data pipelines • JavaScript (Required) — ES6+, async/await, REST API consumption; you can build and read it confidently • HTML & CSS (Required) — semantic HTML5, responsive layouts; you can build and maintain UI without a framework if needed • SQL & Database Fundamentals (Required) — write queries, design schemas, understand relational vs. non-relational trade-offs • System integrations — connecting platforms via APIs, webhooks, or third-party services, with solid grasp of auth, error handling, and data contracts • Git — branching, PRs, code reviews; you work cleanly in a team repository • AI & Agentic Systems Foundations • Active use of AI-assisted coding tools (Cursor, GitHub Copilot, or similar) in your day-to-day workflow — not optional • Working knowledge of LLM APIs (OpenAI, Anthropic, or Groq) — calling endpoints, structuring prompts, parsing responses • Understanding of prompt engineering basics: system prompts, few-shot examples, temperature, and output formatting • Familiarity with tool/function calling patterns — how LLMs invoke external tools or APIs to take actions • Automation platforms: Zapier, Make, or n8n — ideally built for real use cases, not just experiments • Agentic framework experience: LangChain, LangGraph, AutoGen, or CrewAI • Vector databases or RAG pipelines (Pinecone, Chroma, Weaviate) — even at a prototype level • Memory and state management patterns for long-running AI agents • PowerBI or data visualization experience • Docker, CI/CD, or cloud (AWS) experience • Low-code platform experience (OutSystems or similar) • React or a modern frontend framework (Vue, Svelte) • One Thing to Know • One Thing to Know • We will dig into your work. If you can explain what you built, why you built it that way, and what you'd do differently — you're exactly who we're looking for. • English communication will be assessed as part of the interview process. Candidates should be prepared for a written exercise and a video call with the U.S.-based hiring team.