Senior Principal AI Engineer

Our Engineering organization is scaling its AI Engineering capabilities under new leadership, creating an opportunity to shape the next generation of AI at Rapid7. We’re looking for Senior Principal AI Engineers to define and influence the technical direction of our LLM and agentic AI systems across the organization. You’ll tackle our most complex technical challenges, establish architectural principles and engineering standards, and drive greenfield innovation that delivers meaningful impact for our global customers. Through technical leadership and mentoring, you’ll shape strategic product and platform investments and influence how we build and scale AI across Rapid7.

About the Team

AI is reshaping cybersecurity on both sides. Attackers can use AI to strike at machine speed, and only AI-powered defense can keep up. At the same time, organizations can only adopt AI with confidence if it is secure. Rapid7 sits at the intersection of security and AI, and we are building industry-defining products for this new era.

Rapid7's AI Engineering team builds the AI that powers our security platform. We are AI engineers and applied scientists who take models from research to production, combining open-source and frontier LLMs, AI agents, and fast predictive models with more than 20 years of Rapid7 security expertise. Our work drives core use cases across Detection and Response, such as alert triage, threat investigation, and automated response, and Exposure and Remediation, such as vulnerability prioritization, attack surface risk assessment, and guided remediation. Together, these help customers stop threats faster and fix what matters most.

About the Role

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.


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About Rapid7

At Rapid7, our vision is to create a secure digital world for our customers, our industry, and our communities. We do this by harnessing our collective expertise and passion to challenge what’s possible and drive extraordinary impact. We’re building a dynamic and collaborative workplace where new ideas are welcome.

Protecting 11,500+ customers against bad actors and threats means we’re continuing to push the envelope just like we’ ve been doing for the past 20 years. If you ’re ready to solve some of the toughest challenges in cybersecurity, we’re ready to help you take command of your career. Join us.

Rapid7, Inc. is committed to fair and equitable compensation practices. A candidate’s salary is determined by various factors including, but not limited to, relevant work experience, skills, and certifications. We evaluate compensation decisions on a case-by-case basis, and it is not typical for an individual to be hired at the very top of the salary range.

The annual salary range for this role, depending on location, is:


United States: $238,200.00 - 322,200.00 USD Annual

Salary ranges may vary based on geographical location. This range does not include variable/incentive compensation, equity and benefits (where applicable/eligible). 

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or any other status protected by applicable national, federal, state or local law.