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AI Engineer (LLM & Agent Systems)
Actively Reviewing
ADScholars
Job Description
About The Job
AI Engineer (Python & Generative AI) Key Responsibilities
We're looking for engineers who are passionate about building AI products and eager to learn. You don't need to be an expert in Kubernetes, multi-agent systems, or advanced cloud architecture from day one. If you have a strong Python foundation, have built interesting LLM-based projects, enjoy working with APIs, and are excited to grow in generative AI, we'd love to hear from you.
AI Engineer (Python & Generative AI) Key Responsibilities
- Design, develop, and maintain AI-powered applications using Python.
- Build AI solutions using Large Language Models (LLMs), LangChain, LangGraph, or similar frameworks.
- Develop and optimise Retrieval-Augmented Generation (RAG) pipelines and semantic search applications.
- Integrate REST APIs, third-party services, and AI models into production-ready applications.
- Build scalable backend services using Python and modern API frameworks such as FastAPI.
- Work with vector databases, embeddings, and document processing pipelines.
- Collaborate with cross-functional teams to prototype, test, and deploy AI-driven features.
- Write clean, maintainable, and well-documented code following software engineering best practices.
- Participate in code reviews, testing, and CI/CD processes.
- Continuously explore and adopt emerging AI tools, frameworks, and best practices.
- 2–3 years of professional experience in Python software development.
- Strong proficiency in Python and object-orientated programming.
- Hands-on experience building AI applications using large language models (LLMs).
- Experience with LangChain, LangGraph, or similar LLM orchestration frameworks through professional or personal projects.
- Experience developing REST APIs using FastAPI or similar Python frameworks.
- Good understanding of Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, and vector search concepts.
- Familiarity with vector databases such as Chroma, FAISS, Pinecone, or :.
- Comfortable integrating APIs, SDKs, and third-party services.
- Familiarity with cloud platforms such as AWS, Azure, or GCP.
- Daily experience using modern AI-assisted development tools such as Cursor or similar AI coding assistants.
- Strong problem-solving skills, curiosity, and a willingness to learn new technologies.
- Personal projects, GitHub repositories, or open-source contributions involving LLMs or AI applications.
- Experience with Docker and basic CI/CD concepts.
- Exposure to React, Next.js, or TypeScript.
- Familiarity with AI evaluation, guardrails, or Model Context Protocol (MCP).
- Experience building AI copilots, chatbots, or workflow automation solutions.
We're looking for engineers who are passionate about building AI products and eager to learn. You don't need to be an expert in Kubernetes, multi-agent systems, or advanced cloud architecture from day one. If you have a strong Python foundation, have built interesting LLM-based projects, enjoy working with APIs, and are excited to grow in generative AI, we'd love to hear from you.
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