AI Solution Architecture
- Design end-to-end Agentic AI architectures for enterprise use cases.
- Define AI architecture standards, governance frameworks, and implementation blueprints.
- Lead AI transformation and modernization initiatives.
- Establish scalable and secure AI platform architecture patterns.
Agentic AI & Multi-Agent Systems
- Design autonomous AI agents with:
- Reasoning
- Planning
- Memory management
- Task execution
- Decision-making
- Define multi-agent orchestration patterns and collaboration frameworks.
- Implement human-in-the-loop (HITL) validation mechanisms.
- Design agent communication protocols and tool integrations.
Generative AI & LLM Engineering
- Evaluate and architect solutions using:
- GPT
- Claude
- Gemini
- Llama
- Mistral
- Open-source foundation models
- Design prompt engineering and prompt orchestration frameworks.
- Architect enterprise RAG solutions.
- Define semantic search and vector retrieval strategies.
AI Platform & Cloud Architecture
- Architect solutions on:
- Azure OpenAI
- Azure AI Services
- AWS Bedrock
- Amazon SageMaker
- Google Vertex AI
- Integrate AI systems with enterprise applications and APIs.
- Design event-driven and cloud-native AI platforms.
AI Governance & Security
- Establish responsible AI governance frameworks.
- Implement AI security controls and model guardrails.
- Manage:
- Prompt injection protection
- Hallucination controls
- Data privacy compliance
- Model governance
LLMOps & AgentOps
- Define deployment and operational frameworks for AI systems.
- Implement monitoring and observability strategies.
- Establish evaluation metrics and AI performance KPIs.
- Drive continuous improvement and feedback loops.