AI Architect
Tasks
- Address bias fairness and transparency
- Build observability stacks
- Create evaluation frameworks
- Deploy AI components to enterprise applications
- Design AI orchestration architecture
- Design AI pipelines
- Detect model drift
- Develop LLM orchestration layers
- Drive responsible AI practices
- Ensure compliance with security standards
- Establish AI governance frameworks
- Evaluate vendors and AI platforms
- Implement IAM and encryption controls
- Implement agent workflows
- Implement agentic AI tool use
- Implement auditability and model risk management
- Implement cost monitoring tools
- Implement retraining pipelines
- Integrate AI APIs and data platforms
- Integrate and deploy AI solutions
- Lead knowledge sharing and enablement
- Manage memory management
- Manage model lifecycle
- Mentor engineers and architects
- Monitor and optimize AI usage costs
- Monitor prompts and model responses
- Optimize inference cost latency and throughput
- Orchestrate multi-agent workflows
- Track vector retrieval quality
- Translate requirements into technical blueprints
- Write Python production code
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | APIs | Agent Orchestration | Agentic AI | Azure | Bias Mitigation | Containerization | Drift Detection | Embeddings | Encryption | Evaluation | Fairness | Fine Tuning | IAM | Kubernetes | LLM orchestration | Langchain | Langgraph | Language Models | Large Language Models | Lifecycle Management | Llamaindex | Model Drift | Model Drift Detection | Model Lifecycle | Model Lifecycle Management | Multi-Agent | Multi-agent orchestration | Observability | Prompt engineering | Python | RAG | Retraining Pipelines | Retrieval-Augmented Generation | Semantic Kernel | Transparency | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Architect | Architect
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