Senior AI ML Engineer

Location Hybrid - New York City Full-time opportunity (No visa sponsorship available at this time) Must have financial industry background We're seeking a Senior AI ML Engineer to design, develop, and deploy innovative AI-powered solutions that transform the way financial services organizations operate. This role is ideal for a hands-on engineer who is passionate about machine learning, Generative AI, large language models (LLMs), and modern cloud technologies. As an AI Engineer, you'll work alongside architects, data scientists, software engineers, product teams, and business stakeholders to build scalable, secure, and production-ready AI applications that drive business value while meeting the regulatory and security requirements of the financial services industry. Develop AI & Generative AI Solutions Design, build, and deploy AI and machine learning solutions that address complex business challenges. Develop and implement Generative AI applications leveraging Large Language Models (LLMs). Build Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources. Develop prompt engineering strategies and optimize model performance. Integrate AI capabilities into existing business applications and digital platforms. Build Production-Ready AI Systems Create scalable APIs and microservices for AI-powered applications. Deploy and manage AI workloads in cloud environments such as Azure, AWS, or Google Cloud. Implement model monitoring, observability, and performance optimization practices. Support MLOps processes, including model deployment, versioning, testing, and lifecycle management. Collaborate Across Teams Partner with architects, data scientists, and engineering teams to deliver end-to-end AI solutions. Work closely with business stakeholders to understand requirements and translate them into technical solutions. Participate in code reviews, design sessions, and technical planning activities. Contribute to AI platform standards, reusable components, and best practices. Ensure Security, Governance, and Compliance Develop solutions that meet financial services security, compliance, and governance requirements. Support responsible AI practices, data privacy controls, and model risk management processes. Ensure solutions adhere to enterprise architecture and cybersecurity standards. Experience Required Qualifications 10+ years of experience in software engineering, machine learning engineering, AI engineering, or related roles. Experience developing and deploying machine learning and AI solutions in production environments. Experience working in Financial Services, Banking, Capital Markets, Wealth Management, FinTech industries. Experience at a hedge fund preferred. Technical Skills Strong programming skills in Python. Experience with AI and machine learning frameworks such as TensorFlow, PyTorch, LangChain, or LlamaIndex. Experience developing applications using Large Language Models (LLMs) and Generative AI technologies. Knowledge of RAG architectures, embeddings, vector databases, and semantic search. Experience building RESTful APIs and microservices. Familiarity with cloud platforms including Microsoft Azure, AWS, or Google Cloud. Experience with SQL and NoSQL databases. Knowledge of Git, CI/CD pipelines, and DevOps practices. Preferred Qualifications Experience with Azure OpenAI, OpenAI APIs, AWS Bedrock, Vertex AI, or similar AI platforms. Experience with Databricks, Snowflake, or modern data platforms. Familiarity with containerization technologies such as Docker and Kubernetes. Understanding of MLOps frameworks and model lifecycle management. Knowledge of AI governance, model monitoring, and responsible AI practices. Experience working with financial data, risk systems, fraud detection, or customer-facing AI applications.