AI/ML Technical Architect Lead (Remote)

Job summary

This role is a senior, hands-on technical leadership position focused on transforming advanced AI and machine learning capabilities into secure, scalable, production-ready solutions. The position involves shaping AI/ML strategy and architecture while directly contributing to model development, deployment, integration, and operationalization.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical discipline; a Master’s degree or PhD is preferred.
• 10+ years of progressive experience in AI/ML, data science, software engineering, advanced analytics, or a closely related field, with substantial hands-on experience in modern AI technologies.
• At least 5 years of hands-on experience designing, developing, and deploying AI/ML solutions in production environments, including MLOps practices.
• Strong programming skills in Python, R, Java, or comparable languages.
• Deep knowledge of machine learning frameworks such as TensorFlow or PyTorch, ideally with AWS SageMaker experience.

Responsibilities

• Lead AI/ML strategy, solution architecture, technical implementation, and modernization initiatives across complex programs.
• Design, develop, integrate, and deploy scalable AI/ML models and intelligent systems.
• Provide hands-on technical leadership throughout the AI/ML development lifecycle.
• Oversee data engineering pipelines, MLOps processes, and model lifecycle management.
• Ensure AI/ML solutions align with risk management and cybersecurity frameworks.
• Collaborate with security teams, business owners, and technical stakeholders.
• Mentor junior engineers and provide technical guidance across multidisciplinary teams.

Skills

• Experience integrating AI/ML solutions into secure enterprise environments.
• Familiarity with AI services such as AWS Bedrock, Azure AI Foundry, or Google Vertex AI.
• Strong communication, stakeholder management, problem-solving, mentoring, and technical leadership skills.

Education

• Bachelor’s degree in a relevant field is required; advanced degrees are preferred.

Tools

• Experience with cloud platforms, preferably AWS, and familiarity with AI governance and responsible AI practices.