Intelligent AI Solutions Architect

2 weeks ago

Bengaluru, Karnataka, India beBeeDataScientist Full time US$ 1,21,656 - US$ 1,53,210
Senior Data Scientist

Job Title: Senior Data Scientist

We are seeking a highly skilled and experienced data scientist to architect agentic AI solutions and own the full ML lifecycle. The successful candidate will operationalise large language models, build agentic workflows, implement MLOps best practices, and design multi-agent systems for cybersecurity tasks.

Key Responsibilities:
  • Operationalise LLMs and agentic workflows 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 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.
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.
Preferred Qualifications:
  • AWS certifications (Solutions Architect, Developer Associate).
  • Experience with Model Context Protocol (MCP) and RAG integrations.
  • Familiarity with workflow orchestration tools (Apache Airflow).

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