Data Scientist – AI Agents

3 weeks ago

Chennai, Tamil Nadu, India CoreStack Full time

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.

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