Senior Principal AI Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Establish the technical vision, architecture, and long-term roadmap for LLM and agentic systems in Detection and Response as well as Exposure and Remediation.

• Formulate a comprehensive model strategy across the organization, incorporating frontier or open-source models, fine-tuning, distillation, post-training, and investment in new capabilities.

• Oversee complex, high-stakes technical projects involving multiple teams.

• Direct the fine-tuning, distillation, and post-training processes for open-source LLMs utilizing security data.

• Set organization-wide standards for context engineering, inference optimization, and evaluation processes.

• Ensure that evaluations serve as the release gate for every AI system that Rapid7 deploys.

• Lead the optimization of LLM inference at scale, maintaining a balance among quality, latency, and cost.

• Conduct design reviews and address complex technical trade-offs.

• Prototype and develop essential model, training, and inference code.

• Mentor and cultivate talent among Principal, Staff, and Senior engineers.

• Develop AI engineering expertise across Rapid7.

• Represent Rapid7’s AI engineering efforts to executives, customers, and the broader community.

• Impact product, platform, and business strategies.

• Shape strategic investments in AI-driven cybersecurity products.

⛳️ Requirements

• A minimum of 14 years of experience in software or ML engineering.

• At least 2 years of experience in developing production LLM or agentic AI systems.

• A PhD in Computer Science, Machine Learning, AI, or a related discipline is preferred, or equivalent expertise demonstrated through industry experience and technical contributions.

• Proven record of building scalable, production-level AI systems and shared platforms utilized across various products.

• Cutting-edge knowledge in LLMs, including transformer architecture, attention mechanisms, tokenization, and positional encodings.

• Advanced skills in PyTorch, encompassing custom model development, mixed precision, and distributed training techniques like FSDP and DeepSpeed.

• Practical experience with fine-tuning and post-training open-weight LLMs, using both full and parameter-efficient methods, such as LoRA and QLoRA.

• Familiarity with distillation techniques and preference or RL-based methods like DPO and GRPO.

• Extensive experience in context engineering, retrieval, memory, and context management for prolonged agent workflows.

• Experience in defining evaluation strategies and benchmarks for LLM and agent systems.

• In-depth knowledge of inference optimization methods, including prefill and decode, KV-cache management, continuous batching, speculative decoding, and quantization.

• Experience serving models at scale using vLLM, SGLang, or TensorRT-LLM.

• Ideally, experience with AWS and GPU kernel development using CUDA or Triton.

• Strong fundamentals in predictive AI, classical ML, distributed systems, and Python.

• Capability to make informed decisions between predictive AI, classical ML, and LLM strategies based on accuracy, latency, and cost considerations.

• Acknowledgment as an AI authority through publications, patents, open-source contributions, or industry involvement.

• Ability to influence technical and product strategies across the organization.

• Skill in aligning Engineering, Product, and other departments on technical direction.

• Capacity to navigate ambiguity and the evolving landscape of AI technology and threats.

• Commitment to Rapid7’s core values.

🏝️ Benefits

• Flexible/remote working arrangements available, as indicated by locations in Belfast and UK Remote.

• Opportunities for technical leadership and mentoring.

• Chance to influence strategic product, platform, and business initiatives.

• Opportunity to engage in innovative AI development from the ground up.

• Professional advancement through the enhancement of AI engineering capabilities.

• A collaborative, multi-faceted team environment.