The Role Senior Python AI Engineer Design and develop backend systems and APIs for AI-powered applications. You will play a key role in building scalable backend systems and APIs, collaborating closely with cross-functional teams to shape the future of data-driven products across various platforms. What we are looking for Strong proficiency in Python (5+ years), including modern frameworks (FastAPI, Flask, or Django). Deep learning frameworks (PyTorch, TensorFlow) for custom modeling beyond LLM APIs. Experience with large language models (LLMs) such as GPT, Gemini, LLaMA, or similar. Experience with prototyping tools: Streamlit, Gradio. Solid experience designing RESTful APIs and microservice architectures. Experience with version control (Git) and CI/CD workflows. Hands‑on experience with containerization (Docker, ideally Kubernetes). Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus. Understanding of security best practices for handling sensitive data. Strong problem‑solving skills to address complex challenges and performance bottlenecks. Excellent technical communication skills to collaborate effectively across teams and explain technical concepts to non‑technical stakeholders. Ability to work independently while aligning with broader team goals. Intermediate‑advanced English level. AI/ML & LLM Ecosystem Experience with vector databases (Pinecone, Weaviate, Milvus, Chroma, FAISS). Hands‑on with LLMs & APIs: OpenAI (GPT‑5/5‑mini), Anthropic Claude, Google Gemini, Meta Llama, Mistral. Familiarity with AWS Bedrock for accessing and deploying foundation models. Prompt engineering and structured output design (JSON mode, function calling). Model fine‑tuning (LoRA, QLoRA) and evaluation frameworks (DeepEval, Ragas). Responsibilities Design and develop backend systems and APIs for AI-powered applications. Build and optimize LLM‑based workflows, including chatbots, copilots, and automation tools. Implement RAG architectures using vector databases and document pipelines. Integrate and orchestrate cloud‑hosted foundation models (AWS Bedrock, OpenAI, Anthropic, Google Gemini, Meta Llama, Mistral). Collaborate cross‑functionally with data scientists, product managers, and frontend developers to deliver end‑to‑end AI products. Ensure performance, scalability, and cost optimization of AI solutions in production environments. Monitor, evaluate, and continuously improve deployed AI systems. What we offer Guaranteed on‑time monthly payments with flexible withdrawal options. Predictable 8‑hour working days, enabling a harmonious work‑life balance. Up to 24 flex days off per year for full‑time positions found through Proxify, without losing pay. Career‑accelerating opportunities at cutting‑edge remote companies. Hand‑picked matches that bypass typical recruitment biases. A single contracting process that opens doors to multiple roles, without additional assessments. Consistent pay every month for positions landed through Proxify. #J-18808-Ljbffr