Junior Artificial Intelligence Engineer

Junior AI Engineer Python programming (strong fundamentals, OOP, writing APIs, debugging). Hands-on experience building GenAI/LLM solutions: RAG / embeddings / vector DB / prompt engineering. Experience with FastAPI or Flask (building and serving APIs). Understanding of LLM application lifecycle (prompting, evaluation, versioning, deployment basics). Knowledge of at least one cloud platform: AWS or Azure. Basic understanding of Git, code reviews, and deployment workflows. Vector databases: Pinecone / Qdrant / Chroma / Weaviate / FAISS. Frameworks: LangChain / LangGraph / LlamaIndex / Semantic Kernel. Evaluation tools: RAGAS / TruLens / DeepEval, prompt testing frameworks. Containerization: Docker (Kubernetes is optional). CI/CD exposure: GitHub Actions / Azure DevOps / Jenkins. Data pipelines: Airflow / Prefect / Databricks. Safety tooling: Presidio, content safety filters, access control patterns. ✅ Key Responsibilities GenAI / LLM Engineering Build LLM-powered applications (chatbots,...