
Artificial Intelligence Architect
2 weeks ago
This is a challenging opportunity to leverage strong expertise in NLP, Computer Vision, and LLM-based agentic systems.
About the RoleAs a GenAI expert, you will have the chance to conceptualize, design, implement, and deploy production-grade LLM agents and multi-modal AI applications that solve real-world business challenges.
Key Responsibilities- Model & Agent Development: Conceptualize, design, and implement LLM-powered agents and NLP solutions tailored to business needs.
- Hands-on Coding & Development: Write, test, and maintain clean, scalable, and efficient Python code for LLMs and AI agents.
- Implement fine-tuning, embeddings, and prompt engineering with a focus on cost, latency, and accuracy.
- Performance & Monitoring: Monitor and optimize LLM agents for latency, scalability, robustness, and explainability.
- Implement observability and guardrails strategies for enterprise-safe AI deployments.
- Research & Innovation: Read, interpret, and implement AI/Agent research papers into practical production-ready solutions.
- Stay ahead of academic and industry trends in Agentic AI, multimodal AI, orchestration frameworks, and evaluation methodologies.
- Debugging & Issue Resolution: Diagnose and resolve model inaccuracies, system integration issues, and performance bottlenecks.
- Apply advanced debugging techniques to troubleshoot deployment errors, data inconsistencies, and unexpected agent behaviors.
- Continuous Learning & Adaptability: Quickly unlearn outdated practices and adapt to emerging GenAI and Agentic AI technologies.
- Contribute to a culture of innovation by experimenting, prototyping, and scaling cutting-edge AI solutions.
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