Senior AI Engineer – LLM Fine-Tuning / Model Engineering

5+ years of enterprise software development, including 2+ years of hands-on AI/GenAI experienceStrong Python development and production AI/LLM engineering experienceProven experience building Generative AI solutions for financial services, including trading, investment operations, research, compliance or productivity use casesDeep hands-on LLM fine-tuning and model adaptation experience: LoRA / QLoRAPEFTSupervised fine-tuningInstruction tuningPreference tuningKnowledge distillationExperience deploying fine-tuned/custom models into production, including containerized inference, GPU infrastructure, model registries and model-serving frameworksStrong model evaluation and benchmarking skills — comparing base, fine-tuned, distilled and RAG approaches using quality, latency, throughput and cost metricsPractical experience with open-weight models, such as Llama, Mistral/Mixtral, Qwen, Gemma, Phi or similarExperience with LangChain, LangGraph and/or Semantic Kernel for GenAI workflows and agentic applicationsStrong Microsoft Azure experience, particularly Azure OpenAI, Azure Machine Learning and Azure Cognitive Search; AWS exposure is a plusStrong RAG, semantic retrieval and conversational memory experienceExperience developing autonomous / agentic AI systemsExperience with Docker, Kubernetes, CI/CD and observability for enterprise AI deploymentAbility to work with quants, traders and business stakeholders and translate business requirements into AI/model solutionsStrong problem-solving, communication, stakeholder management and Agile delivery skillsBachelor's/Master's degree in Computer Science or equivalent experienceThis role has a much stronger model-engineering focus, particularly around fine-tuning, open-source models, evaluation/benchmarking and production deployment of customized models.