Remote Data Scientist/AI Engineer - INTL

We are seeking a hands-on Data Scientist/AI Engineer/ML Engineer to design, build, evaluate, and deploy customer-facing LLM applications-with a primary focus on retrieval-augmented generation (RAG), agentic workflows, and production-grade Azure deployments.

This role will be responsible for delivering a web-enabled, customer-facing chatbot that combines proprietary knowledge with live web search, integrates securely with enterprise systems, and meets high standards for accuracy, reliability, observability, and safety.

This is not a research-only role. You will write production code, build evaluation harnesses, and own models and services from prototype through live deployment.

4+ years of experience in Data Science, Machine Learning Engineering, or AI Engineering, with recent hands-on work in Generative AI / LLMs.

-Strong proficiency in Python for production-grade ML and AI services.

-Demonstrated experience building RAG-based LLM applications beyond simple demos or notebooks.

-Hands-on experience with vector databases or vector search systems (e.g., Azure AI Search, Pinecone, FAISS, etc.).

-Practical experience with prompt engineering, prompt chaining, and agent/tool orchestration.

-Experience designing LLM evaluation frameworks and quality metrics-not just manual testing.

Azure & Cloud Experience

-Production experience with Azure OpenAI and Azure-based AI services.

-Experience deploying AI/ML services using Azure-native infrastructure (Functions, App Services, Containers, CI/CD).

-Familiarity with observability and telemetry for AI systems (logging, metrics, tracing).

LLM Application Engineering

-Experience integrating external tools, APIs, or web search into LLM workflows.

-Understanding of LLM limitations, failure modes, and mitigation strategies.

-Ability to design systems that balance accuracy, latency, cost, and safety. -Experience with LangChain, Semantic Kernel, LlamaIndex, or similar orchestration frameworks.

-Experience with hybrid search (keyword + vector) and reranking strategies.

-Familiarity with responsible AI, content filtering, and prompt safety patterns.

-Experience building customer-facing chatbots or conversational AI systems at scale.

-Background in NLP, information retrieval, or applied ML research.