Senior AI Engineer

• Design, implement, and iterate on named agents, including orchestration patterns, hand-offs, planning loops, tool use, and shared memory
• Contribute to model training and fine-tuning across data curation, supervised fine-tuning (SFT), preference optimization (DPO/GRPO/RLHF-style), and evaluation
• Extend the co-evolutionary self-training (Javelin) loop so the system improves from its engagements
• Build self-improvement systems (false-positive detection, tiered skill learning, agent directives, code-patch proposals) and pipelines for human approval
• Design security-specific evaluations covering OWASP Top 10, exploit chaining, finding accuracy, and agent reliability; track performance over model and agent changes
• Contribute to multimodal (vision) and mobile (iOS/Android) coverage and BYOK support efforts
• Own production reliability: latency, cost, observability, failure-mode analysis, and Kubernetes-based deployment
• Improve customer-facing accuracy surfaces and live accuracy gauges exposed to customers

• 5+ years building production ML/AI systems, including at least 2 years working directly on LLMs or LLM-powered agents
• Deep Python and strong production engineering practices (testing, code review, observability)
• Hands-on fine-tuning experience: SFT, preference optimization (DPO, GRPO, RLHF/RLAIF), data curation, and synthetic data generation
• Strong grasp of transformer architectures and training stack (PyTorch, Hugging Face, DeepSpeed or FSDP, accelerate)
• Experience designing and shipping multi-agent or tool-using LLM systems in production
• Rigorous evaluation design experience: building harnesses, tracking experiments, and data-driven decision making
• Inference optimization experience (vLLM, TensorRT-LLM, quantization, throughput/latency tradeoffs)
• Familiarity with retrieval pipelines, vector stores, and structured memory for agents
• Kubernetes and containerized deployment fluency
• Genuine interest in offensive security and the ability to ramp quickly on OWASP Top 10, API/web/mobile pentesting concepts

Here’s What Else Might Help You Out

• Offensive security certifications or experience (OSCP/OSWE/OSWA, CTF, bug bounty, red team)
• Research publications at top ML/security venues or open source contributions to agent/LLM tooling
• Experience with adversarial ML or red-teaming AI systems
• Familiarity with mobile app reverse engineering or binary analysis

$150,000 - $220,000 a year - Full-time, Pulled from the full job description

• 401(k)
• Health insurance
• Vision insurance
• Dental insurance, * 401(k)
• Dental insurance
• Health insurance
• Vision insurance