Generative AI Engineer

🔍 Now Hiring: Principal Generative AI Scientist (Financial Services Domain) 📍 Location: Fulltime on-site Monday to Friday in Mclean 🕒 Employment Type: Contract / Full-time Are you ready to push the boundaries of Generative AI in a highly regulated and data-rich environment? We're seeking a Principal Gen AI Scientist to lead the development of innovative AI Agents, Agentic Workflows, and GenAI Applications that drive real business impact in the financial services industry. This is a hands-on role where you'll work at the cutting edge of AI — applying advanced techniques in LLMs, RAG, Graph RAG, multimodal AI, evaluation frameworks, and AWS cloud solutions — to build scalable, enterprise-grade solutions. 🔧 What You'll Do • Architect, design, and implement AI Agents and Agentic Workflows for real-world, high-value use cases. • Build and optimize lightweight LLMs; evaluate and integrate models like Claude, Azure OpenAI, and open-source alternatives. • Develop Retrieval Augmented Generation (RAG) systems and Graph RAG solutions using vector databases. • Curate enterprise knowledge bases via AWS Bedrock, Elastic, and other tools. • Drive integration of MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication into AI workflows. • Collaborate with cross-functional teams — including product managers, designers, full-stack engineers, and data engineers — to create full-stack GenAI products. • Deploy production-grade GenAI solutions with evaluation frameworks, guardrails, and bias mitigation. • Build data pipelines to extract, chunk, anonymize, and enrich data from unstructured formats like PDFs, video, and audio. • Lead multimodal orchestration for AI using frameworks such as Apache Spark, PySpark, and MLFlow/Kubeflow on AWS EKS. • Map media content to vector representations and integrate with platforms like AWS Knowledge Base, Elastic, and MongoDB Atlas. ✅ What We’re Looking For • MS/PhD in AI, Machine Learning, Data Science, or a related field. • 10+ years of AI/ML experience, with 3+ years in applied GenAI/LLM solutions. • Proven expertise in: • Prompt engineering • LLM fine-tuning and deployment • RAG/Graph RAG architectures • Multimodal model development • Vector databases and embeddings • Cloud-native ML pipelines (AWS, SageMaker, Bedrock, EKS) • Strong programming skills: Python, Jupyter, Transformers, LangChain, etc. • Solid understanding of GenAI system design patterns, evaluation frameworks, and MLOps best practices. • Ability to operate in a fast-paced, agile, and collaborative environment. • Must provide a GitHub or public code repository demonstrating recent GenAI work. ⭐ Preferred Qualifications • Published research or patents in GenAI/LLM/ML domains. • Experience with AI governance, bias mitigation, and secure GenAI deployments. • Built and deployed full-stack GenAI applications using MCP, A2A, and Graph RAG in production. • Familiarity with CI/CD workflows and scalable inference APIs. 📌 Important: Candidates must demonstrate hands-on GenAI experience — including prompt design, model deployment, building agents, and handling unstructured data at scale. GitHub repositories or code samples are required as part of the application. Interested in making a real impact with GenAI? Apply now and be part of a transformative journey in the financial services industry. 🔗 [Apply Now] #GenAI #LLM #AIJobs #PromptEngineering #RAG #GraphRAG #AWS #MachineLearning #FinTech #Python #MLOps #DataScienceJobs