Senior Quant Developer

We are seeking an experienced remote Senior Quantitative Developer with expertise in AI/ML, financial systems, and enterprise software development. This role is ideal for a hands-on engineer who can build AI-powered financial applications, develop scalable APIs, and collaborate with cross-functional teams to deliver innovative solutions.Must-Have Qualifications7+ years of software development experienceStrong experience building APIs and AI-powered applicationsExpert programming skills in Python with experience in Java, C++, or Scala1–3 years of experience in financial services or FinTechExperience developing applications using LLMs; experience with AI agents/agentic AI is highly preferredExperience with cloud platforms (AWS, Azure, or GCP) and modern software engineering practicesBachelor's degree preferred (Master's or PhD in a quantitative field is a plus)Key ResponsibilitiesDesign, develop, and deploy AI/ML solutions for financial applicationsBuild and optimize LLM, NLP, and generative AI applicationsDevelop scalable APIs, microservices, and distributed systemsCreate data pipelines and implement MLOps best practices for model deployment and monitoringDevelop quantitative models, financial analytics, and simulation toolsBuild real-time market data processing and financial analytics solutionsWrite production-quality, scalable, and maintainable codeCollaborate with business stakeholders, quants, data engineers, and product teamsRequired Technical SkillsLanguages: Python, Java, C++, Scala, SQLAI/ML: PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, LLMsCloud & DevOps: AWS, Azure, or GCP; Docker, Kubernetes, CI/CDData: Spark, Kafka, Airflow, PostgreSQL, MongoDB, RedisExperience with REST APIs, microservices, Git, and modern development workflowsPreferred QualificationsExperience with RAG architectures, LLM fine-tuning, and AI agentsKnowledge of quantitative finance, derivatives, risk management, or portfolio analyticsExperience with financial engineering libraries (QuantLib, pandas, NumPy)Familiarity with MLOps tools such as MLflow or Weights & BiasesCFA, FRM, or other financial certifications are a plusExperience with reinforcement learning, real-time streaming, or low-latency systems is a plus