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Rapid7 Logo Rapid7 · IT - Software Development

Principal AI/ML Engineer

India, Pune · Job Posted March 19, 2026
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Job Description

Rapid7 is seeking a Principal AI Engineer to lead the architectural evolution of our AI Center of Excellence. In this role, you will design and own the end-to-end distributed systems that make advanced ML, LLMs, and agentic AI reliable, scalable, and secure at an enterprise level. The AI Center of Excellence leverages advanced ML and agentic AI systems to protect our customers’ attack surfaces by embedding intelligence into real-world security workflows. We operate in ambiguous problem spaces, valuing technical rigor and principled decision-making to deliver production-grade AI at scale.

Job Responsibility

  • Own the end-to-end system architecture for AI, ML, and Agentic platforms, ensuring they are reliable, scalable, and secure
  • Design complex data ingestion pipelines, feature stores, and inference microservices that bridge the gap between research and production
  • Establish architectural standards and reference patterns for LLM orchestration, RAG systems, and multi-agent workflows
  • Lead architectural reviews as the final technical authority, making critical trade-offs across accuracy, latency, cost, and reliability

Requirements

  • Exceptional ability to reason at the system and architecture level to make long-term technical decisions
  • Courageous and principled decision-making when navigating high-stakes, ambiguous problem spaces
  • Proven mentorship of Staff and Senior engineers, fostering growth in architectural thinking and technical rigor
  • Accountability for the long-term technical health and security of AI systems across multiple teams
  • 13+ years of experience in Data Science, ML Engineering, or Applied AI with a focus on large-scale systems
  • Hands-on mastery of LLM orchestration frameworks such as LangChain and LangGraph for agentic workflows
  • Deep expertise in designing RAG pipelines and managing vector database retrieval at scale
  • Advanced proficiency in AWS ecosystems, specifically Bedrock, SageMaker, EKS, and Lambda
  • Expertise in MLOps standards, including model registries, drift detection, and automated retraining frameworks
  • Strong background in deep learning for NLP and sequence-based problems like malware behaviour modelling
  • Proficiency in Infrastructure as Code (Terraform) and CI/CD for ML workloads
  • Experience implementing robust guardrails and evaluation frameworks (e.g., Promptfoo, HELM) for autonomous systems
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