AES - DE - Generative AI Solution Architect
Tasks
- Conduct discovery workshops and solution reviews
- Debug non deterministic agent outputs systematically
- Define agent topology memory strategy and state machines
- Deploy agent based systems to production environments
- Design multi-agent orchestration systems
- Evaluate new models frameworks and tooling
- Guide review and ship code generated by AI
- Implement retrieval-augmented generation pipelines
- Implement tool routing and fallback handling
- Integrate agent systems with enterprise APIs
- Integrate agents with enterprise data platforms
- Mentor junior AI engineers and raise engineering quality
- Own end to end delivery of AI native programs
- Perform systematic evaluation of agent outputs
- Prepare technical proposals POC plans and roadmaps
- Run agentic coding workflows with CLI tools
- Translate business problems into agent architectures
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | Agent systems | Claude Code | CrewAI | Cursor | Device deployment | Embeddings | Enterprise systems | Evaluation | Fallback Handling | Fine Tuning | Generative AI | Langchain | Langgraph | Langsmith | MCP | Memory Strategy | Model Context Protocol | Multi-Agent | Multi-Agent Systems | Non Deterministic Debugging | On-device Deployment | OpenAI Codex | RAG | Reranking | Retrieval-Augmented Generation | State machines | Tool Routing | Vector Databases
Education
N/A
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