Job Details

Data Scientist/AI Engineer/ML Engineer

We are seeking a hands-on Data Scientist/AI Engineer/ML Engineer to design, build, evaluate, and deploy customer-facing LLM applicationswith 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.

Skills and Requirements:

• 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 metricsnot 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.