AI Engineer
Tasks
- Analyze business requirements and translate into AI solutions
- Collaborate with business teams to identify and prioritize AI use cases
- Configure access control and data protection for AI solutions
- Continuously evaluate generative AI technologies and trends
- Define internal standards for AI use
- Design and implement generative AI solutions
- Develop and optimize prompts conversation templates and AI workflows
- Document AI solutions and underlying architectures
- Ensure AI solutions comply with security privacy and regulatory requirements
- Implement RAG over internal and external data sources
- Implement logging monitoring alerting and cost control
- Implement rag architectures using vector databases
- Integrate LLM models into enterprise ecosystem
- Monitor performance costs and accuracy of AI solutions
- Provide knowledge transfer to IT and business teams
- Provide production technical support and maintenance
- Test generated responses for accuracy robustness and hallucination reduction
Perks/Benefits
- Collaborative innovation driven work environment
- Meal tickets
- Private health insurance
- Professional development opportunities
- Safe workplace with modern tools
- Work-life balance
Skills/Tech-stack
API Development | AWS Bedrock | Azure AI | Chatbot Development | Embeddings | Google Vertex | Google Vertex AI | LLM API | Langchain | Langgraph | Llamaindex | Microservices | Prompt engineering | Python | RAG | Vector Database | Vertex AI
Education
Roles
AI | AI Engineer | Engineer
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