Senior Principal AI Engineer

As a Senior Principal AI Engineer, you will set the technical direction for how Rapid7 builds, tunes and serves LLMs and agentic systems across its security products. You understand LLMs from the ground up, from transformer internals and training to fine-tuning and inference optimization, and you stay hands-on with the hardest problems. You know where LLMs shine and where they fall short, and you treat them as one tool in the AI toolbox, alongside predictive AI and classical ML, choosing the right approach for each problem. Specifically your focus will be to:

• Set the AI technical vision, architecture and multi-year roadmap for LLM and agentic systems across Detection and Response and Exposure and Remediation
• Define company-wide model strategy, including when to use frontier or open-source models, when to fine-tune, distill or post-train, and where to invest in new capabilities
• Lead the most complex and highest-risk technical initiatives across multiple teams, including fine-tuning, distillation and post-training of open-source LLMs on security data
• Establish company-wide standards for context engineering, inference optimization and evaluation, with evals as the release gate for every AI system we ship
• Lead optimization of LLM inference at scale, balancing quality, latency and cost
• Lead design reviews, resolve the most complex technical trade-offs, and stay hands-on by prototyping and building critical model, training and inference code
• Mentor and develop Principal, Staff and Senior engineers, building the depth of AI engineering talent across Rapid7
• Represent Rapid7’s AI engineering to executives, customers and the external community, influencing product, platform and business strategy

The skills and qualities you’ll bring include:

• 14+ years of software or ML engineering experience, including 2+ years building production LLM or agentic AI systems. A PhD in Computer Science, Machine Learning, AI or a related field is preferred, or equivalent depth of expertise demonstrated through industry experience and technical contributions
• A track record of building scalable, production-grade AI systems and shared platforms adopted across multiple products, with company-wide impact through technical leadership, mentoring and standards
• Leading-edge expertise in LLMs, including transformer architecture, attention, tokenization and positional encodings, and how models are trained and served, with advanced PyTorch skills spanning custom model code, mixed precision and distributed training (e.g., FSDP, DeepSpeed)
• Hands-on fine-tuning and post-training of open-weight LLMs, including full and parameter-efficient methods (LoRA, QLoRA), distillation, and preference or RL-based methods (e.g., DPO, GRPO), ideally including experience training LLMs from scratch
• Deep experience with context engineering (retrieval, memory, and context management for long-running agent workflows) and with defining evaluation strategy and benchmarks for LLM and agent systems
• Deep knowledge of inference optimization, including prefill and decode, KV-cache management, continuous batching, speculative decoding and quantization, and serving at scale with vLLM, SGLang or TensorRT-LLM, ideally on AWS and including GPU kernel work (CUDA or Triton)
• Strong predictive AI, classical ML, distributed systems and Python fundamentals, with the judgment to make efficient, transparent decisions between these approaches and LLMs based on accuracy, latency and cost
• Takes accountability for organization-wide technical outcomes, proactively addressing systemic risks and removing barriers to delivery while ensuring technical decisions align with strategic priorities
• An influential communicator who can articulate complex architectural trade-offs, build consensus and influence technical and product decisions across the organization
• Builds alignment across Engineering, Product and other functions on technical direction, driving decisions that shape product and platform investments.
• Anticipates evolving customer needs and shapes AI architecture and technical strategy to maximize customer value, making informed trade-offs between capability, performance, cost and scalability to guide product and platform investment
• Thrive in ambiguity at the leading edge of AI, driving change and focusing forward as the technology and the threat landscape evolve
• Recognition as an expert in AI, evidenced by publications, patents, open-source contributions or industry engagement
• Embody our core values to foster a culture of excellence that drives meaningful impact and collective success.

We know that the best ideas and solutions come from multi-dimensional teams. That’s because these teams reflect a variety of backgrounds and professional experiences. If you are excited about this role and feel your experience can make an impact, please don’t be shy - apply today.