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 operationalize LLMs, build Agentic workflows, implement MLOps best practices, and design multi-agent systems for cybersecurity tasks.

Key Responsibilities

- Operationalize 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 containerized with Docker and Kubernetes.
- Monitor models and infrastructure through CloudWatch, Prometheus, and Grafana; analyze performance and optimize 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.
- Solid 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.

Skills: Terraform, MLops, Aws, Python

Experience: 4.00-8.00 Years

📌 Senior Data Scientist - AgenticAI (Bengaluru)
🏢 Securonix Consultancy
📍 Bengaluru