Staff AI Engineer

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

📋 Description

• Design, develop, and deploy LLM and agentic AI systems within Rapid7’s security offerings.

• Take ownership of technical solutions from inception to completion for the designated area.

• Spearhead the design and architecture of AI systems in Detection and Response as well as Exposure and Remediation.

• Contribute to the formulation of the technical roadmap.

• Suggest model strategies, incorporating the use of frontier or open-source models, as well as fine-tuning, distillation, and post-training processes.

• Fine-tune, distill, and post-train open-source LLMs using security data from the curation stage through deployment.

• Enhance context engineering, inference optimization, and evaluation methodologies.

• Optimize inference for quality, latency, and cost efficiency.

• Establish evaluations as critical checkpoints for the release of AI systems.

• Conduct design reviews and resolve intricate technical trade-offs.

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

• Provide mentorship to engineers and collaborate with Product and platform teams.

• Lead AI initiatives or programs and decompose larger objectives into actionable milestones.

• Manage technical risks and interdependencies across teams.

• Convert customer requirements into scalable AI solutions.

⛳️ Requirements

• Over 8 years of experience in software or ML engineering, with at least 2 years dedicated to building production-level LLM or agentic AI systems.

• A Master’s degree in Computer Science, Machine Learning, AI, or a related discipline is preferred, or equivalent practical experience.

• Proven track record in leading scalable, production-grade AI systems utilized by various teams or products.

• Profound understanding of LLMs, encompassing transformer architecture, attention mechanisms, tokenization, positional encodings, training, and serving.

• Advanced skills in PyTorch, including custom model coding, training loops, mixed precision, and distributed training techniques such as FSDP and DeepSpeed.

• Practical experience in fine-tuning and post-training of open-weight LLMs, involving methods like LoRA, QLoRA, distillation, DPO, and GRPO.

• Familiarity with context engineering, retrieval, memory, context management, and LLM/agent evaluation benchmarks.

• Strong understanding of inference optimization techniques, KV-cache management, continuous batching, speculative decoding, quantization, and serving at scale with tools like vLLM, SGLang, or TensorRT-LLM.

• Solid foundational knowledge in predictive AI, classical ML, distributed systems, and Python.

• Experience in leading AI projects or programs of moderate scope and complexity.

• Ability to manage risks and dependencies effectively and drive issues to resolution.

• Capacity to articulate complex technical concepts and trade-offs to both technical and non-technical stakeholders.

• Proficient in building cross-functional partnerships and aligning technical strategies.

• Skillful in translating customer needs into scalable, commercially viable AI solutions.

• A strong commitment to Rapid7’s core values.

🏝️ Benefits

• Variable/incentive compensation (excluded from stated salary range).

• Equity (where applicable/eligible).

• Benefits (where applicable/eligible).

• Fair and equitable compensation practices.

• A collaborative workplace that fosters new ideas.