AI Architect

Boston Energy Trading and Marketing LLC; Boston (MA); On-site; USD 180,000 - 230,000; Full time

Job summary

Boston Energy Trading and Marketing LLC is seeking an AI Strategy & Architecture leader to define and govern the enterprise AI roadmap in Boston, ensuring alignment with business goals and technology roadmaps. You will design scalable, secure AI platforms and data pipelines, and mentor cross-functional teams.

The role requires 8+ years in software/data/ML with hands-on ML framework experience, cloud services across Azure/AWS/GCP, MLOps, and strong communication with executives.

Qualifications

• 8+ years in Software Eng, Data Eng, or ML, incl. 3+ years in AI leadership.
• Hands-on with ML frameworks and real-world AI/ML deployments.
• Experience with RAG, LLM orchestration, and agent-based workflows.
• Proficient in Python and SQL; another language is a plus.
• Strong knowledge of CI/CD, MLOps, and model governance.
• Understanding security, privacy, and compliance requirements.

Responsibilities

• Define and maintain enterprise AI architecture aligned with goals and roadmaps.
• Lead scalable, secure AI/ML systems, platforms, and data pipelines.
• Evaluate AI tech, frameworks, and cloud services for solutions.
• Develop reference architectures and governance models for AI/ML.
• Architect end-to-end AI/ML solutions from data to deployment and monitoring.
• Partner with product, data, and engineering to translate business problems.
• Oversee MLOps and CI/CD pipelines for models.
• Establish standards for model lifecycle, versioning, observability, tuning.
• Collaborate on data models, ETL/ELT, and real-time streaming architectures.
• Design AI platforms using cloud technologies (Azure preferred).
• Ensure AI systems meet security, privacy, and reliability standards.
• Provide technical leadership and mentorship to teams.
• Stay current with AI research and industry practices.
• Communicate complex concepts to executives and non-technical stakeholders.

Skills

AI Architecture

MLOps

Cloud Platforms

Python

SQL

Data Engineering

Security & Compliance

Communication

Leadership

ML Frameworks

Docker/Kubernetes

Education

Bachelor’s or Master’s in CS/DS/Engineering

Tools

Azure ML

AWS Sagemaker

GCP Vertex AI

Job description

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