AI Architect

Key Responsibilities AI Strategy & Architecture Define and maintain the enterprise AI architecture, ensuring alignment with organizational goals and technology roadmaps. Lead the design of scalable, robust, and secure AI/ML systems, platforms, and data pipelines. Evaluate and select AI technologies, frameworks, cloud services, and tools to support solution development. Develop reference architectures, best practices, and governance models for AI and ML solutions. Solution Design & Delivery Architect end-to-end AI/ML solutions—from data ingestion and feature engineering to model deployment and monitoring. Partner with product, data, and engineering teams to translate business problems into AI-based solutions. Oversee MLOps implementation, ensuring continuous integration/continuous delivery (CI/CD) pipelines for machine learning models. Establish and enforce standards for model lifecycle management, versioning, observability, and performance tuning. Collaborate with data engineers to design data models, ETL/ELT pipelines, and real-time streaming architectures. Architect AI platforms using cloud technologies (Azure preferred; AWS or GCP experience a plus). Ensure AI systems meet enterprise standards for security, privacy, compliance, and reliability. Provide technical leadership, mentorship, and guidance to AI engineers, data scientists, and cross-functional teams. Champion AI innovation by staying current with emerging technologies, research advancements, and industry practices. Communicate technical concepts to executives, business stakeholders, and non-technical audiences. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field. 8+ years of experience in Software Engineering, Data Engineering, or Machine Learning, including 3+ years in an AI architecture leadership role. Hands-on expertise with: Machine learning frameworks (TensorFlow, PyTorch, Scikit learn, LangChain) Time-series modeling and forecasting Real-world experience implementing: RAG systems LLM orchestration pipelines Agent-based AI workflows AI/ML cloud services (Azure Machine Learning, AWS Sagemaker, or GCP Vertex AI) Distributed systems and container orchestration (Docker, Kubernetes) Strong knowledge of MLOps, CI/CD, and model governance frameworks. Proficiency with Python, SQL, and at least one other programming language. Understanding of security, compliance, data governance, and responsible AI practices. Preferred Qualifications Experience with large language models (LLMs), vector databases, and generative AI. Experience integrating AI into: Trader tools Risk and analytics platforms Experience with: Vector databases and semantic search Feature stores and model registries LLM evaluation, guardrails, and observability Technical leadership or architecture ownership across teams Certifications in cloud architecture (Azure, AWS, GCP). Experience implementing real-time AI and high-scale distributed systems. Familiarity with enterprise architecture frameworks (TOGAF, Zachman). Energy trading firms, utilities, IPPs, or commodities trading Optimization models or market simulation frameworks Additional Qualifications Strategic thinking with an innovative mindset Strong problem-solving and analytical skills Excellent communication and stakeholder management Ability to lead and influence without authority Passion for emerging AI technologies and continuous learning #J-18808-Ljbffr Boston Energy Trading and Marketing LLC