Job
Description
As a highly skilled Data Scientist specializing in AI agents, generative AI, and knowledge engineering, you will be responsible for enhancing AI-driven cloud governance solutions at our company. Your role will involve advancing multi-agent systems, leveraging LLMs, and integrating knowledge graphs (OWL ontologies) in a Python environment. Your contributions will directly impact FinOps, SecOps, CloudOps, and DevOps by providing scalable, AI-enhanced decision-making, workflows, and monitoring. **Key Responsibilities:** - Design, develop, and optimize LLM-based multi-agent systems for cloud governance. - Implement agent collaboration using frameworks like LangChain, AutoGen, or open-source MAS architectures. - Develop adaptive AI workflows to improve governance, compliance, and cost optimization. - Apply generative AI techniques (e.g., GPT-4, Google Gemini, fine-tuned BERT models) to knowledge representation and reasoning. - Design and manage knowledge graphs, OWL ontologies, and SPARQL queries for intelligent decision-making. - Enhance AI agent knowledge retrieval using symbolic reasoning and semantic search. - Develop embedding-based search models for retrieving and classifying cloud governance documents. - Fine-tune BERT, OpenAI embeddings, or custom transformer models for document classification and recommendation. - Integrate discrete event simulation (DES) or digital twins for adaptive cloud governance modeling. - Work with multi-cloud environments (AWS, Azure, GCP, OCI) to extract, analyze, and manage structured/unstructured cloud data. - Implement AI-driven policy recommendations for FinOps, SecOps, and DevOps workflows. - Collaborate with CloudOps engineers and domain experts to enhance AI-driven automation and monitoring. **Required Qualifications:** - 4+ years of experience in Data Science, AI, or Knowledge Engineering. - Extensive knowledge or experience in Knowledge Engineering is preferred. - Strong proficiency in Python and relevant ML/AI libraries (PyTorch, TensorFlow, scikit-learn). - Hands-on experience with knowledge graphs, OWL ontologies, RDF, and SPARQL. - Expertise in LLMs, NLP, and embedding-based retrieval (OpenAI, Cohere, Hugging Face models). - Familiarity with multi-agent systems, LangChain, AutoGen, or similar frameworks. - Experience working with cloud platforms (AWS, Azure, GCP) and AI-driven cloud governance. **Preferred Qualifications:** - Experience with knowledge-driven AI applications in cloud governance, FinOps, or SecOps. - Understanding of semantic search, symbolic AI, or rule-based reasoning. - Familiarity with event-driven architectures, digital twins, or discrete event simulation (DES). - Background in MLOps, AI pipelines, and cloud-native ML deployments. In addition to the exciting technical challenges and responsibilities outlined above, you will have the opportunity to work on cutting-edge AI agent ecosystems for cloud governance in a collaborative environment where AI, knowledge engineering, and cloud automation converge. We offer competitive compensation, benefits, and flexible work arrangements including remote/hybrid options. If you thrive in a fast-paced environment, demonstrate intellectual curiosity, and have a passion for applying advanced AI techniques to solve real-world cybersecurity challenges, we encourage you to apply.,
