About the Role
Role details below.
Responsibilities
- Design and define the end-to-end architecture for AI and machine learning solutions across the organization.
- Lead the design, development, and deployment of scalable AI systems, including predictive models, generative AI, and intelligent automation.
- Define AI platform architecture including data pipelines, model training environments, MLOps frameworks, and model deployment strategies.
- Collaborate with data scientists, data engineers, and software engineers to translate business requirements into scalable AI solutions.
- Evaluate and select appropriate AI/ML frameworks, tools, and cloud services to support enterprise AI initiatives.
- Establish best practices for model development, governance, monitoring, and lifecycle management.
- Design architectures for integrating AI capabilities into enterprise applications, APIs, and business workflows.
- Ensure AI solutions meet requirements for performance, scalability, security, and compliance.
- Lead technical decision-making related to model infrastructure, LLM integration, vector databases, and AI orchestration frameworks.
- Drive the adoption of responsible AI practices, including model explainability, bias mitigation, and ethical AI principles.
- Guide teams on AI architecture patterns such as RAG (Retrieval Augmented Generation), AI agents, and multi-model orchestration.
- Support AI innovation by evaluating emerging technologies and identifying opportunities for competitive advantage.
Benefits
- Contractor model
- Remote model
- Salary in $USD
- Paid Vacations
- Day off for birthdays
- Benefits courses and/or certifications
- Opportunity to work wit
Work Arrangement
Remote (Country)