AI Engineering Lead
Tasks
- Advise technical and non-technical stakeholders
- Build AI agent workflows
- Build Retrieval Augmented Generation systems
- Build production ready AI solutions
- Collaborate with cross-functional teams
- Define AI first software development standards
- Deploy AI models to cloud
- Design AI solution architecture
- Develop AI driven microservices
- Develop generative AI applications
- Develop machine learning systems
- Ensure security, scalability, and code quality
- Evaluate emerging technologies
- Implement LLMOps pipelines
- Implement MLOps pipelines
- Lead AI engineering team
- Mentor engineers
- Monitor model performance
- Optimize latency and cost
- Set AI engineering best practices
- Support AI delivery roadmap
Perks/Benefits
- Career advancement
- Exposure to emerging technologies
- Fully remote
- Professional development
- Work-life balance
Skills/Tech-stack
AI Observability | AWS | Azure | CI/CD | Cost Control | Docker | Generative AI | Google Cloud | Kubernetes | LLMOps | Langchain | Language Models | Large Language Models | Latency management | Llamaindex | MLOps | Machine Learning | Model Monitoring | Performance optimization | PyTorch | Python | Retrieval-Augmented Generation | TensorFlow | Vector Databases
Education
N/A
Roles
AI | AI Engineering | AI Engineering Lead | Engineer | Engineering Lead | Lead | Learning Engineer | Machine Learning Engineer
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