- Lead the design, development, and deployment of complex AI solutions, including LLM-based applications, retrieval pipelines, and model-driven services
- Own technical direction for major components or domains within AI platforms or products
- Drive engineering best practices for model evaluation, testing, monitoring, and operationalization
- Partner with product, data, and business stakeholders to translate requirements into scalable AI solutions
- Contribute to architecture decisions, including model selection, system integration, and API design
- Ensure solutions meet enterprise standards for security, privacy, and responsible AI
- Mentor and guide engineers, contributing to team capability and engineering quality
- Identify technical risks and implement appropriate mitigation strategies
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field
- Significant experience delivering production AI/ML systems, including model deployment and operationalization
- Strong proficiency in programming languages such as Python, TypeScript, or Rust
- Experience with AI/ML frameworks, LLM technologies, and data pipelines
- Knowledge of model lifecycle management, MLOps, and production reliability practices
- Demonstrated ability to lead complex technical initiatives
- Strong problem-solving skills and ability to work across disciplines
Core Competencies
Demonstrates expertise in leading the design and deployment of AI solutions, with a strong focus on model lifecycle management, operationalization, and adherence to enterprise standards for security and responsible AI. Proven ability to mentor engineers and drive engineering best practices across AI platforms.
Highest-signal resume keywords
- AI Solution Design
- Model Deployment
- MLOps
- Python Programming
- Technical Leadership
ATS Optimization Keywords
Hard Skills
- AI/ML Frameworks
- LLM Technologies
- Data Pipelines
- Model Lifecycle Management
- Operationalization
Soft Skills
- Problem-Solving
- Mentoring
Industry Keywords
- Engineering Best Practices
- Technical Direction
- API Design
- Security Standards
- Privacy Standards
Tools & Technologies
- TypeScript
- Rust