Senior GenAI Engineer
Tasks
- Build LLM-powered workflows
- Build MCP multi cloud platform tooling
- Create benchmark datasets
- Create secure execution environments for AI agents
- Design Generative AI applications
- Detect hallucinations
- Develop agentic AI solutions
- Develop evaluation and testing frameworks
- Enable audit capabilities for AI agents
- Implement human-in-the-loop workflows
- Implement memory management for AI agents
- Implement model routing and fallback mechanisms
- Implement network restrictions for AI workloads
- Implement observability for AI systems
- Implement retrieval-augmented generation pipelines
- Integrate external knowledge sources
- Manage permissions and secrets handling
- Manage token usage optimization
- Optimize prompt management
- Orchestrate AI context
- Run regression testing for AI systems
- Set up tracing logging monitoring
Perks/Benefits
- Childcare assistance
- Continuous learning opportunities
- Discounts through partner programs
- Extended parental leave
- Extended parental leave benefits
- Gym access
- Health and dental insurance
- Language learning platforms
- Life insurance coverage
- Meal and food allowance
- Parenting and family support programs
- Professional development resources
- Profit sharing
- Wellness partnerships
- Wellness resources
Skills/Tech-stack
AWS | Agentic AI | Amazon Bedrock | Audit Logging | Authentication | Azure | Azure OpenAI | CI/CD | Cloud platform | Databricks | Docker | Evaluation Frameworks | Generative AI | Google Cloud | Google Cloud Platform | Hallucination mitigation | Kubernetes | Langchain | Language Models | Large Language Models | Logging | MLOps | Machine Learning | Monitoring | Network Security | Observability | Prompt engineering | Python | Retrieval-Augmented Generation | Secrets management | Token Management | Tracing | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | GenAI Engineer | Senior GenAI Engineer
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