Cloudberry360
Qualification: Bachelor's Degree in Computer Science
Experience: 4+ Years
We’re looking for an experienced and driven Applied AI Engineer to design, build, and deploy intelligent LLM-driven systems with real-world impact. This role sits at the intersection of advanced AI research and robust software engineering, bringing agentic AI to enterprise use cases such as risk monitoring, cost analysis, and system integration. Responsibilities
Agentic Workflows: Build and deploy agentic LLM workflows that automate risk monitoring, cost optimization, and decision-making tasks Multi-Agent Collaboration: Design safe and robust multi-agent systems that include features like conflict resolution, self-reflection, and task prioritization Benchmarking & Evaluation: Develop and maintain benchmarking suites to evaluate agent behavior, safety, robustness, and performance across multiple domains Enterprise Integration: Build tooling that connects large language models to enterprise systems—e.g., ERP platforms, CRMs, and proprietary APIs Stakeholder Collaboration: Work closely with product managers, executives, and end users to gather requirements, demo prototypes, and ensure high-value delivery Required Skills and Experience
Experience: Minimum 2 years of hands-on experience deploying large language models (LLMs) into production environments, with proven guardrailing, monitoring, and evaluation processes Technical Proficiency: Exceptional computer science fundamentals with the ability to architect and implement complex AI systems efficiently Engineering Skills: Proficiency in Python and deep experience with libraries and tools such as LangChain, OpenAI APIs, Hugging Face, or similar agentic frameworks System Design: Strong background in system architecture, API integrations, and working with enterprise data pipelines or automation stacks Safety & Governance: Deep understanding of prompt engineering, model fine-tuning, and AI safety best practices in applied settings We aim to be a leading innovator in designing, building, and supporting critical business management solutions on cloud platforms that will help transform your organization and align with your business goals.
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Experience: 4+ Years
We’re looking for an experienced and driven Applied AI Engineer to design, build, and deploy intelligent LLM-driven systems with real-world impact. This role sits at the intersection of advanced AI research and robust software engineering, bringing agentic AI to enterprise use cases such as risk monitoring, cost analysis, and system integration. Responsibilities
Agentic Workflows: Build and deploy agentic LLM workflows that automate risk monitoring, cost optimization, and decision-making tasks Multi-Agent Collaboration: Design safe and robust multi-agent systems that include features like conflict resolution, self-reflection, and task prioritization Benchmarking & Evaluation: Develop and maintain benchmarking suites to evaluate agent behavior, safety, robustness, and performance across multiple domains Enterprise Integration: Build tooling that connects large language models to enterprise systems—e.g., ERP platforms, CRMs, and proprietary APIs Stakeholder Collaboration: Work closely with product managers, executives, and end users to gather requirements, demo prototypes, and ensure high-value delivery Required Skills and Experience
Experience: Minimum 2 years of hands-on experience deploying large language models (LLMs) into production environments, with proven guardrailing, monitoring, and evaluation processes Technical Proficiency: Exceptional computer science fundamentals with the ability to architect and implement complex AI systems efficiently Engineering Skills: Proficiency in Python and deep experience with libraries and tools such as LangChain, OpenAI APIs, Hugging Face, or similar agentic frameworks System Design: Strong background in system architecture, API integrations, and working with enterprise data pipelines or automation stacks Safety & Governance: Deep understanding of prompt engineering, model fine-tuning, and AI safety best practices in applied settings We aim to be a leading innovator in designing, building, and supporting critical business management solutions on cloud platforms that will help transform your organization and align with your business goals.
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