Data Scientist – AI Agents & Knowledge Engineering

CoreStack is hiring a Data Scientist specializing in AI agents and knowledge engineering to enhance AI-driven cloud governance solutions. The role involves developing multi-agent systems, utilizing generative AI, and managing knowledge graphs in Python. Candidates should have over 3 years of experience in Data Science, proficiency in Python, and familiarity with cloud platforms. The position offers competitive compensation and flexible work arrangements, including remote options.
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.