Architect – Agentic AI Engineering
Summary
Architect for agentic AI systems: designs Python backend services, builds multi-step AI agent workflows with LLMs, deploys on AWS/Azure, and refines AI prototypes into scalable production systems with prompt engineering, observability, and documented APIs.
- Apply software architecture principles and design patterns
- Architect backend services in Python
- Build multi step tool using AI agents
- Design agentic AI workflows
- Design and deploy solutions on AWS and Azure
- Design documented APIs
- Develop prompt engineering strategy
- Ensure security cost efficiency and scalability
- Evaluate and integrate LLM capabilities
- Implement testing observability error handling and versioning
- Make and document architectural decisions
- Optimize latency and throughput
- Refactor AI prototypes into production systems
- Remediate technical debt and scalability bottlenecks
- Set technical standards and provide architectural guidance
- Test and iterate LLM prompts