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Data Scientist – AI Agents
4 weeks ago
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
- 3+ years of experience in Data Science, AI, or Knowledge Engineering .
- 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.
