Data Scientist – Agentic AI

3 weeks ago

Kozhikode, Kerala, India RemoteStar Full time

Job Title: Data Scientist – Agentic AI & MLOps

Location: Bangalore - Hybrid (3 days work from office, 2 days from home)

About Us:

Our client delivers next-generation security analytics and operations management. They secure organisations worldwide by staying ahead of cyber threats, leveraging AI-reinforced capabilities for unparalleled protection.

Job Overview:

We're seeking a Senior Data Scientist to architect agentic AI solutions and own the full ML lifecycle—from proof-of-concept to production. You'll operationalise LLMs, build agentic workflows, implement MLOps best practices, and design multi-agent systems for cybersecurity tasks.

Key Responsibilities:

  • Operationalise large language models and agentic workflows (LangChain, LangGraph, LlamaIndex, Crew.AI) to automate security decision-making and threat response.
  • Design, deploy, and maintain multi-agent AI systems for log analysis, anomaly detection, and incident response.
  • Build proof-of-concept GenAI solutions and evolve them into production-ready components on AWS (Bedrock, SageMaker, Lambda, EKS/ECS) using reusable best practices.
  • Implement CI/CD pipelines for model training, validation, and deployment with GitHub Actions, Jenkins, and AWS CodePipeline.
  • Manage model versioning with MLflow and DVC, set up automated testing, rollback procedures, and retraining workflows.
  • Automate cloud infrastructure provisioning with Terraform and develop REST APIs and microservices containerised with Docker and Kubernetes.
  • Monitor models and infrastructure through CloudWatch, Prometheus, and Grafana; analyse performance and optimise for cost and SLA compliance.
  • Collaborate with data scientists, application developers, and security analysts to integrate agentic AI into existing security workflows.

Qualifications:

  • Bachelor's or Master's in Computer Science, Data Science, AI or related quantitative discipline.
  • 4+ years of software development experience, including 3+ years building and deploying LLM-based/agentic AI architectures.
  • In-depth knowledge of generative AI fundamentals (LLMs, embeddings, vector databases, prompt engineering, RAG).
  • Hands-on experience with LangChain, LangGraph, LlamaIndex, Crew.AI or equivalent agentic frameworks.
  • Strong proficiency in Python and production-grade coding for data pipelines and AI workflows.
  • Deep MLOps knowledge: CI/CD for ML, model monitoring, automated retraining, and production-quality best practices.
  • Extensive AWS experience with Bedrock, SageMaker, Lambda, EKS/ECS, S3 (Athena, Glue, Snowflake preferred).
  • Infrastructure as Code skills with Terraform.
  • Experience building REST APIs, microservices, and containerization with Docker and Kubernetes.
  • Solid data science fundamentals: feature engineering, model evaluation, data ingestion.
  • Understanding of cybersecurity principles, SIEM data, and incident response.
  • Excellent communication skills for both technical and non-technical audiences.

Preferred Qualifications:

  • AWS certifications (Solutions Architect, Developer Associate).
  • Experience with Model Context Protocol (MCP) and RAG integrations.
  • Familiarity with workflow orchestration tools (Apache Airflow).
  • Experience with time series analysis, anomaly detection, and machine learning.

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