Role Overview:
This is a strategic, customer-facing architecture role focused on Enterprise AI and Agentic AI transformation. The selected candidate will design enterprise-grade AI solutions, build multi-agent orchestration frameworks, lead AI discovery workshops, engage with C-level stakeholders, and drive AI initiatives from strategy and PoC through production deployment.
Key Responsibilities:
- Architect end-to-end AI and Agentic AI solutions.
- Design multi-agent systems using LangGraph, AutoGen, CrewAI, Semantic Kernel, and related frameworks.
- Build RAG-based enterprise AI architectures with vector databases and knowledge graphs.
- Integrate AI solutions with SAP, Salesforce, Microsoft 365, ServiceNow, Oracle, and other enterprise platforms.
- Lead customer workshops, AI discovery sessions, and executive stakeholder engagements.
- Drive AI governance, responsible AI, security, compliance, and observability initiatives.
- Mentor engineering teams and contribute to AI practice development and innovation.
Required Technical Skills:
- Generative AI, LLMs, Prompt Engineering, Fine-tuning Techniques
- Agentic AI Frameworks: LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel
- RAG Architecture, Vector Databases, Knowledge Graphs
- Azure OpenAI, AWS Bedrock, Google Vertex AI
- Python, FastAPI, LlamaIndex, LangChain
- Docker, Kubernetes, CI/CD
- AI Monitoring and Observability Tools
- Enterprise System Integration (SAP, Salesforce, Microsoft, ServiceNow)
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