Digital AI Development Engineer
Tasks
- Apply cybersecurity guidance to requirements
- Automate deployments with infrastructure-as-code
- Build and manage CI/CD pipelines
- Build scalable reliable secure AI services
- Characterize system level risks
- Collaborate with cross-functional teams
- Deploy AI models
- Design AI pipelines for data ingestion
- Design distributed scalable AI architectures
- Develop and manage embeddings databases for semantic search
- Develop embeddings databases
- Develop recommendations for leadership
- Document AI pipeline workflows and best practices
- Implement recommendation systems
- Implement semantic search
- Integrate AI solutions with cloud platforms
- Plan system testing and evaluation
- Process data for AI models
Perks/Benefits
- 401k plan
- Dental insurance
- Flexible work schedules
- Medical insurance
- Paid leave
- Tuition reimbursement
- Vision insurance
Skills/Tech-stack
AWS Bedrock | Agile | Amazon SageMaker | Angular | Ansible | Azure Foundry | CI/CD | CSS | CircleCI | Cloud platform | Continuous Deployment | Continuous integration | Cybersecurity | Distributed Systems | Django | Docker | Embeddings | Express.js | GitLab CI | Go | Google Cloud | Google Cloud Platform | HTML | Java | JavaScript | Jenkins | Kubernetes | Langchain | Linux | MLOps | MongoDB | MySQL | Node.js | Open WebUI | PostgreSQL | Python | REST API | React | Recommendation Systems | Scalable Architecture | Semantic Search | Software Assurance | Spring Boot | System Administration | Terraform | Vue.js | Windows System Administration | Windows system | Zero Trust
Education
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