Associate AI Engineer
Explicitly calls for a "vibe coding" approach — fast iteration, quick validation, ship-and-learn mindset for rapid prototyping.
About the Role
Associate AI Engineer working on AI-native applications, integrating LLMs and building end-to-end features across backend, frontend, and AI workflows. The role focuses on rapid prototyping, REST API and dashboard development, and implementing RAG and embedding-based solutions under senior guidance.
Job Description
Role
Associate AI/ML Engineer (1–2 years experience) responsible for building and shipping AI-native applications and features across backend, frontend, and AI integrations. The role emphasizes execution: integrating LLM APIs, implementing prompt engineering, supporting RAG workflows, and delivering production-ready REST APIs and responsive frontend components.
Key Responsibilities
- Design and develop AI-native applications end-to-end (backend + frontend) under senior guidance.
- Build and maintain REST APIs and backend services using Python frameworks (FastAPI, Flask).
- Integrate LLM APIs (OpenAI, Claude, Hugging Face) and implement prompt engineering techniques.
- Support RAG-based workflows using embeddings and vector databases; integrate external data sources.
- Develop custom dashboards, internal tools, and micro apps powered by AI insights.
- Build responsive frontend components using React, Next.js, or similar frameworks.
- Rapidly prototype ideas with a fast-iteration “vibe coding” approach for quick validation.
- Debug AI pipelines, backend workflows, and data-processing tasks; work with databases like PostgreSQL and Supabase.
- Collaborate with product, business, and engineering teams to convert requirements into working AI features.
Requirements
- 1–2 years of experience in software development, AI/ML, backend development, or related roles (strong internships considered).
- Strong Python fundamentals and hands-on coding experience.
- Experience with backend frameworks such as FastAPI or Flask.
- Working knowledge of frontend development using React, Next.js, or similar.
- Hands-on experience integrating LLM APIs (OpenAI, Claude, Hugging Face) in real applications.
- Knowledge of prompt engineering and practical LLM usage patterns.
- Understanding of RAG, embeddings, and vector search concepts; familiarity with vector DBs like Pinecone, FAISS, Supabase Vector.
- Experience in REST API development and backend integrations; familiarity with PostgreSQL and Supabase.
- Comfort with data handling using Pandas and NumPy.
- Strong problem-solving, debugging skills, ownership mindset, and good communication.
Good to Have
- Experience with LangChain, LlamaIndex, or similar AI orchestration frameworks.
- Exposure to AI-native UX patterns (chat interfaces, copilots, assistants).
- Familiarity with fast prototyping tools and workflows (v0, Bolt, Lovable, Cursor, Claude Code).
- Web scraping experience, basic system design understanding, and deployment experience (Vercel, Railway, Render).
- Understanding of authentication and security basics.