AI Engineer / AI Architect
COP 60000K-71400K (estimate) Senior-level Full Time
Tasks
- Architect data ingestion feature engineering and model serving
- Build training evaluation and deployment workflows
- Collaborate with product engineering and executives on AI roadmaps
- Communicate technical strategy to non technical audiences
- Conduct code reviews
- Create Architecture Decision Records
- Define AI system architecture
- Define evaluation metrics and validation processes
- Design end to end AI pipelines and agent orchestration
- Design modular extensible AI platforms
- Enable real time model observability
- Enforce engineering standards
- Ensure AI system reliability observability and performance
- Implement LLMOps best practices
- Improve iteration velocity with tooling
- Improve retrieval augmented generation performance
- Lead ML system design and implementation
- Make architectural tradeoffs for performance scalability cost complexity
- Manage prompt versioning
- Mentor AI engineers
- Operationalize prototypes into production systems
- Optimize distributed inference systems
- Plan rollout strategies
- Set up CI CD for AI pipelines
- Translate AI opportunities into technical approaches
Perks/Benefits
- N/A
Skills/Tech-stack
CI/CD | Cloud Computing | Compliance | Data Ingestion | Deep learning | Distributed Systems | Evaluation | Feature Engineering | Inference | Infrastructure as Code | Lifecycle Management | MLOps | Machine Learning | Model Lifecycle | Model Lifecycle Management | Model Serving | Monitoring | Observability | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | Secure Software | Secure Software Development | Software development | Training pipelines | “as-code”
Education
N/A
Roles
AI | AI Architect | AI Engineer | Architect | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
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