Senior Data Scientist - Agentic AI & MLOps

4 - 9 years

3 - 15 Lacs

Posted:2 weeks ago| Platform: Foundit logo

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Skills Required

Work Mode

On-site

Job Type

Full Time

Job Description

Role Summary:

Architect and operationalize Agentic AI solutions, managing the full ML lifecycle from proof-of-concept to production. Build multi-agent AI systems for cybersecurity tasks, implement MLOps best practices, and integrate AI workflows into security operations.

Key Responsibilities:

  • Operationalize large language models and Agentic workflows to automate threat response
  • Design, deploy, and maintain multi-agent AI systems for log analysis, anomaly detection, and incident response
  • Build GenAI proof-of-concepts and production-ready components on AWS using Bedrock, SageMaker, Lambda, EKS/ECS
  • Implement CI/CD pipelines for ML with GitHub Actions, Jenkins, and AWS CodePipeline
  • Manage model versioning, automated testing, rollback procedures, and retraining workflows
  • Automate cloud infrastructure with Terraform, build REST APIs, and containerize microservices with Docker and Kubernetes

Minimum Requirements:

  • Bachelor's or Master's in Computer Science, Data Science, AI, or related discipline
  • 4+ years of software development, 3+ years in LLM-based/Agentic AI architectures
  • Strong knowledge of generative AI fundamentals, embeddings, vector databases, prompt engineering, and RAG
  • Hands-on experience with LangChain, LangGraph, LlamaIndex, Crew.AI, or equivalent frameworks
  • Python proficiency and production-grade coding for data pipelines and AI workflows
  • Deep MLOps knowledge including CI/CD for ML, model monitoring, automated retraining, and production-quality best practices
  • Extensive AWS experience, Terraform, Docker, Kubernetes, and REST API development
  • Understanding of cybersecurity principles, SIEM data, and incident response

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Securonix Consultancy logo
Securonix Consultancy

Computer and Network Security

Plano Texas

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