Senior Python AI Engineer
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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.
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