AI Product Engineer
Tasks
- Build MVP end-to-end
- Collect user feedback
- Create user stories
- Define success metrics
- Deploy to production
- Design AI agent prompting
- Design APIs
- Develop frontend/backend services
- Elicit use cases and functional requirements
- Evaluate AI agent outputs
- Gather business requirements
- Implement tool function calling
- Integrate data models
- Maintain production solutions
- Manage acceptance criteria
- Manage product backlog
- Manage requirements traceability
- Model data requirements
- Monitor production systems
- Optimize cost and performance
- Orchestrate AI agents
- Oversee testing implementation
- Perform verification and validation
- Prioritize requirements
- Propose functional improvements
- Select and implement development tools
- Translate requirements into technical specifications
Perks/Benefits
- N/A
Skills/Tech-stack
API Design | AWS | Anthropic SDK | Azure | CI/CD | CrewAI | Docker | GCP | GDPR | GraphQL | JavaScript | LLMOps | Langchain | Langgraph | MLOps | Node.js | Observability | OpenAI API | Prompt engineering | Python | RAG | REST | React | Relational databases | Vector Databases
Education
N/A
Roles
AI | AI Product Engineer | Developer | Engineer | Full Stack | Full Stack Developer | Product Engineer | Stack Developer
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