AI Engineer – LLMs, Agents & RAG

November 13

Apply Now

Receive Emails with Similar Jobs

EY

WebsiteLinkedInAll Job Openings

Finance • Consulting • Technology

EY is a global professional services firm, widely recognized for providing audit, tax, consulting, and advisory services. It focuses on helping its clients solve complex problems and transform their businesses using data and technology. EY is committed to building a better working world by enhancing trust in financial markets and economies globally. Its services include corporate finance advisory, transaction strategy, technology consulting, and more, catering to sectors such as health, energy, finance, government, and more. EY also emphasizes sustainability and innovation in its solutions.

10,000+ employees

Founded 1989

💸 Finance

📋 Description

• Design and implement the intelligence layer of multi-agent systems • Collaborate with team members to build, integrate, and deploy secure AI agents powered by LLMs and RAG on Azure • Develop and maintain LLM- and RAG-based AI agents using Azure OpenAI, LangChain/Semantic Kernel, and Azure ML • Collaborate with the Full Stack Developer to integrate agent endpoints into web and backend applications • Work with DevSecOps to ensure secure deployment, monitoring, and version control of AI components • Implement vector search pipelines (Azure Cognitive Search, FAISS, or Pinecone) • Optimize model inference for latency, accuracy, and scalability • Participate in daily standups, sprint reviews, and code reviews as part of the dev team.

🎯 Requirements

• 1–2 years’ experience developing AI or NLP applications in Python • Hands-on experience with LLMs, prompt engineering (Crafting and optimizing), and RAG design • Experience designing RAG pipelines for enterprise search or document intelligence • Knowledge of vector databases (e.g., Qdrant, Chroma) • Knowledge of document chunking, embedding models, and context window optimization • Familiarity with metadata-based retrieval and re-ranking strategies • Understanding of agent architectures • Ability to orchestrate multiple agents for collaborative or role-based tasks • Strong understanding of transformer architectures (GPT, LLaMA, Mistral, Claude, etc.) • Experience with LLM fine-tuning and prompt engineering • Familiarity with inference optimization, quantization (e.g., bitsandbytes), and deployment techniques • Hands-on experience using OpenAI, Hugging Face Transformers, or LangChain • Knowledge of model evaluation metrics (e.g., perplexity, hallucination rate, factual consistency) • Prior experience deploying LLM-based agents or RAG systems in production is a major plus • Familiarity with Azure AI Services, Azure ML, Azure Functions, and APIs • Understanding of data security, versioning, and MLOps principles • Strong collaboration skills within cross-functional agile teams.

🏖️ Benefits

• support and coaching • opportunities to develop new skills and progress your career • freedom and flexibility to handle your role in a way that’s right for you • Continuous learning • Success as defined by you • Transformative leadership • Diverse and inclusive culture • recruitment and career opportunities to all, regardless of gender, sexual orientation, social background or disability