AI/ML Engineer (W2 Only)

#W2 Only (In-person Interview is required in Iselin, NJ) Overview: AI/ ML Engineer will leverage advanced AI models and Azure OpenAI services to develop innovative solutions for investment banking processes. The ideal candidate will have a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Key Responsibilities: • Develop autonomous AI agents capable of planning, decision-making, and executing tasks to achieve specified user goals, with an emphasis on Python code generation for automation processes. • Develop and Deploy LLM-Based Agents: Build scalable AI agents leveraging frameworks like LangChain, LangGraph, and custom runtimes to facilitate complex workflows and interaction models. • Integration with External APIs & Services: Orchestrate AI agents to communicate seamlessly with enterprise APIs, databases, and cloud services, ensuring smooth operation within complex ecosystems. • Create and optimize end-to-end pipelines for training, testing, and deploying models in production environments such as Azure ML, ensuring robustness and scalability. • Utilize Microsoft Azure OpenAI services to build and optimize AI models. • Contribute to building multi-agent architectures fostering emergent behaviors, robustness, and trustworthiness for autonomous operations. • Ensure compliance with data security, privacy policies, and industry regulations. • Stay updated with the latest trends and advancements in AI, especially related to RAG and Azure OpenAI. Qualifications: • 10+ years of relevant experience in AI/ML, with at least 2 years focused on agentic AI, autonomous systems, or multi-agent architectures • Hands-on experience with multi-agent systems, emergent behavior modeling, and ensuring system robustness and trustworthiness. • Proven experience in investment banking or financial services. • Good experience in Natural Language Processing (NLP) • Extensive hands-on experience with Microsoft Azure OpenAI services. • Strong understanding and practical experience with Retrieval-Augmented Generation (RAG). • Proficiency in programming languages such as Python. • Experience in deploying scalable, production-ready AI solutions integrated within enterprise environments • Knowledge of AI model deployment and API integration. Preferred Qualifications: • Certifications in Azure or AI-related fields. • Experience with large language models (LLMs) and their application in finance. • Prior experience in developing secure and scalable AI solutions.