Senior Python AI Engineer

The

Role: We are looking for a

Senior Python AI Engineer to join our fast-growing Network, who will design and develop backend systems and APIs for AI-powered applications. You will play a key role in designing and 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. • Strong backend development expertise, including databases (SQL/NoSQL). • Experience with version control (Git) and bolthires/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. • Time zone: CET (+/- 3 hours).

We are unable to consider applications from candidates in other time zones. AI/ML & LLM Ecosystem: • LLM orchestration frameworks: LangChain, LangGraph, LlamaIndex. • Retrieval-Augmented Generation (RAG) pipeline design. • Experience with vector databases (Pinecone, Weaviate, Milvus, Chroma, FAISS). • Hands-on with LLMs & APIs: OpenAI (GPT-5/5-mini), Anthropic Claude, bolthires 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, bolthires 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 bolthires optimization of AI solutions in production environments. • Monitor, evaluate, and continuously improve deployed AI systems. What we offer: Get paid, not played No more unreliable clients. Enjoy on-time monthly payments with flexible withdrawal options. Predictable project hours Enjoy a harmonious work-life balance with consistent 8-hour working days with clients. Flex days, so you can recharge Enjoy up to 24 flex days off per year without losing pay, for full-time positions found through Proxify.

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