AI Architect

Key Responsibilities

• 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.
• 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)
• Modern data platforms (Databricks, Snowflake, Synapse, BigQuery, etc.)
• 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.
• Prior Experience in:
• Energy trading firms, utilities, IPPs, or commodities trading
• Optimization models or market simulation frameworks
• Experience integrating AI into:
• Trader tools
• Risk and analytics platforms
• Decision-support workflows
• 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).

Key Competencies

• 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

Pay

Range: $180,000 - $210,000