Job
Description
Job Summary: We are seeking a highly skilled Data Scientist with expertise in AI agents, generative AI, and knowledge engineering to enhance our AI-driven cloud governance solutions. This role focuses on advancing multi-agent systems, leveraging LLMs, and integrating knowledge graphs (OWL ontologies) in a Python environment . You will work at the intersection of machine learning, AI-driven automation, and cloud governance , helping to design intelligent agents that adapt dynamically to cloud ecosystems. Your contributions will directly impact FinOps, SecOps, CloudOps, and DevOps by providing scalable, AI-enhanced decision-making, workflows, and monitoring. Key Responsibilities AI Agent Development Enhancement 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. Generative AI Knowledge Engineering 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 . Machine Learning NLP 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. Cloud Governance Automation 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 is 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 . What We Offer Opportunity to work on cutting-edge AI agent ecosystems for cloud governance. A collaborative environment where AI, knowledge engineering, and cloud automation converge. Competitive compensation, benefits, and flexible work arrangements (remote/hybrid) .The ideal candidate will thrive in a fast-paced environment, demonstrate intellectual curiosity, and have a passion for applying advanced AI techniques to solve real-world cybersecurity challenges.
