Python Full Stack/AI Engineer (Full Remote)

Role Description: Senior AI/ML Engineer (Remote) We are seeking a talented Senior AI/ML Engineer to architect and deploy production-grade AI systems. In this role, you will focus heavily on Large Language Models (LLMs), advanced RAG pipelines, and building scalable, high-performance machine learning infrastructure. This position combines deep hands-on technical execution with client-facing collaboration, converting early-stage AI prototypes into dependable, enterprise-ready systems. --- 🛠️ Key Responsibilities - RAG & Search Architecture: Design, implement, and optimize Retrieval-Augmented Generation (RAG) pipelines and vector embedding workflows. - LLM Integration: Connect, fine-tune, and orchestrate various models (OpenAI, Anthropic/Claude, open-source alternatives) for specific business use cases. - System Optimization: Proactively improve system latency, minimize API costs, and maximize response accuracy in live environments. - Evaluation & Testing: Build and maintain rigorous frameworks to assess retrieval precision, mitigate hallucinations, and track performance benchmarks. - Cloud Deployment: Package and deploy scalable AI services across major cloud infrastructures (AWS, GCP, or Azure). --- 📋 Position Requirements - Must-Have (Core Criteria) - Timezone Alignment: Ability to work within or maintain a significant overlap with EST (US Eastern Time) business hours. - Communication Skills: Excellent, structured English communication. You must be comfortable explaining architectural choices and leading technical discussions. - Reliability: High responsiveness and steady availability during agreed-upon working hours. - Technical Skills & Experience - 5+ years of professional software engineering experience, with a proven track record of shipping AI/ML solutions to production. - Deep understanding of Python backend engineering and modern software architecture. - Hands-on experience building production-grade RAG systems and managing vector databases (Pinecone, Qdrant, Weaviate, FAISS, etc.). - Practical expertise in prompt engineering and LLM orchestration. - Familiarity with cloud platforms (AWS/GCP/Azure) and fundamental ML metrics (cost, latency, precision/recall trade-offs). - Nice-to-Have - Practical use of orchestration tools like LangChain, LlamaIndex, or custom agentic frameworks. - Experience with model fine-tuning or quantization. - Prior work in NLP, search engines, or recommendation systems. - Experience navigating technical constraints in high-scale APIs, Enterprise SaaS, Fintech, or Healthcare sectors. --- 💼 Compensation & Contract - Format: Contract-based, fully remote. - Duration: Long-term potential based on performance and impact. --- 🎯 Ideal Candidate Profile We value engineers who look beyond the algorithmic layer to understand real-world system constraints. The ideal candidate doesn't just build models; they balance cost, speed, and accuracy to deliver maintainable software. If you combine technical depth with strong execution and communication, we want to hear from you.