AI Architect – Agentic Systems (LLM & Multi-Agent Solutions)
Rosario, Santa Fe, Argentina
CAD 146K-175K (estimate) Senior-level Full Time
Tasks
- Define memory strategies for agents
- Define model cost security and privacy guardrails
- Design multi-agent architectures
- Establish observability and tracing for agents
- Evaluate and improve LLM reliability and accuracy
- Implement feedback loops for agent behavior
- Integrate AI into core enterprise systems
- Integrate LLM agents with APIs and tools
- Integrate LLM agents with enterprise data platforms
- Integrate LLM agents with operational workflows
- Lead agentic systems from PoC to production
- Orchestrate and coordinate agent workflows
- Train teams on scalable AI best practices
Perks/Benefits
- Career coaching
- Career development programmes
- Coaching and Mentorship
- Conferences and events
- Employee assistance programme
- Flexible working hours
- Hybrid work
- Training and workshops
- Wellbeing programme
Skills/Tech-stack
AI Foundry | AWS | Agent coordination | Agent coordination patterns | Agent systems | Amazon Bedrock | Azure | Azure AI | Azure AI Foundry | Context grounding | Coordination Patterns | Distributed Systems | Feedback loop | Function Calling | GCP | Google Vertex | Google Vertex AI | Information Retrieval | LLM orchestration | Language Models | Large Language Models | Memory Management | Multi-Agent | Multi-Agent Systems | Observability | Python | RAG | Retrieval optimization | Semantic similarity | Software Architecture | Task decomposition | Tokenization | Tool use | Tracing | Transformer Architecture | Vector embeddings | Vertex AI
Education
N/A
Roles
AI | AI Architect | Architect | Learning Architect | Machine Learning Architect
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