1 day ago
Belfast, United KingdomStaff+
Responsibilities
- Set the AI technical vision, architecture, and multi-year roadmap for LLM and agentic systems across Rapid7’s security products.
- Define company-wide model strategy, including model selection, fine-tuning, distillation, post-training, and new capability investments.
- Lead complex, high-risk initiatives involving fine-tuning, distillation, post-training, evaluation, and inference optimization of LLMs.
- Establish standards for context engineering, evaluation, benchmarks, and release gates for AI systems.
- Optimize LLM inference at scale across quality, latency, and cost constraints.
- Lead design reviews, resolve complex technical trade-offs, and prototype or build critical model, training, and inference code.
- Mentor Principal, Staff, and Senior engineers and build AI engineering capability across the organization.
- Represent AI engineering to executives, customers, and the external community while influencing product, platform, and business strategy.
Requirements
- 14+ years of software or ML engineering experience, including 2+ years building production LLM or agentic AI systems.
- Track record of building scalable, production-grade AI systems and shared platforms adopted across multiple products.
- Leading-edge knowledge of LLMs, including transformer architecture, attention, tokenization, positional encodings, training, and serving.
- Advanced PyTorch skills, including custom model code, mixed precision, and distributed training with technologies such as FSDP and DeepSpeed.
- Hands-on experience with full and parameter-efficient fine-tuning, LoRA, QLoRA, distillation, DPO, GRPO, and preferably training LLMs from scratch.
- Deep experience with context engineering, retrieval, memory, long-running agent workflows, evaluation strategy, and benchmarking for LLM and agent systems.
- Deep knowledge of inference optimization, including prefill and decode, KV-cache management, continuous batching, speculative decoding, quantization, and large-scale serving.
- Experience with vLLM, SGLang, or TensorRT-LLM, ideally on AWS, including GPU kernel work with CUDA or Triton.
- Strong predictive AI, classical ML, distributed systems, and Python fundamentals.
- Ability to lead organization-wide technical outcomes, influence architecture and product decisions, communicate complex trade-offs, and build cross-functional alignment.
- Recognition as an AI expert through publications, patents, open-source contributions, or industry engagement.
- 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.
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About Rapid7
Rapid7 builds a cloud security operations platform and services for enterprises, combining vulnerability management, detection and response (SIEM/XDR and MDR), application security testing, and security automation. Its Insight platform products include InsightVM, InsightIDR, InsightAppSec, and InsightConnect, sold as subscriptions with optional managed services. Founded in 2000 and headquartered in Boston, the NASDAQ-listed company (RPD) serves more than 11,500 customers worldwide.