[Remote] Senior AI Engineer (US)

Note: The job is a remote job and is open to candidates in USA. Assail is a company focused on autonomous offensive security solutions, and they are seeking a Senior AI Engineer for their Ares platform. The role involves developing AI agents and models that enhance the platform's capabilities in security across various applications.ResponsibilitiesDesign, implement, and continuously improve the behavior and prompting of Ares' named agents, including orchestration patterns, hand-offs, planning loops, tool use, and shared memoryContribute to the model powering Ares across data curation, SFT, preference optimization (DPO/GRPO-style), and evaluation. Own pieces of the training pipeline from dataset construction through evalExtend the co-evolutionary self-training system that lets Ares learn from its own engagements and improve over timeBuild false-positive detection, tiered skill learning (suppression rules, agent directives, code-patch proposals), and the infrastructure that routes proposed changes through human approval and back into the platformDesign rigorous, security-specific evaluations covering OWASP Top 10 coverage, exploit chaining, finding accuracy, and agent reliability. Track performance over every model and agent changeContribute to vision capabilities, mobile (iOS/Android) coverage, and BYOK support shipping in Sidewinder and beyondOwn latency, cost, observability, and failure-mode analysis for agents running in customer engagements. Partner with the platform team on Kubernetes-based deploymentContribute to the live accuracy gauge and other surfaces where model and agent quality is exposed to customersSkills5+ years building production ML/AI systems, with at least 2 years working directly on LLMs or LLM-powered agentsDeep Python; strong, production-grade engineering practices (testing, code review, observability)Hands-on fine-tuning experience: SFT, preference optimization (DPO, GRPO, RLHF/RLAIF), data curation, and synthetic data generationStrong grasp of transformer architectures and the modern training stack (PyTorch, Hugging Face, DeepSpeed or FSDP, accelerate)Experience designing and shipping multi-agent or tool-using LLM systems in production — not just demosRigorous eval design: building harnesses, tracking experiments, and making model/agent decisions based on data rather than vibesInference optimization experience: vLLM or TensorRT-LLM, quantization, throughput/latency tradeoffsComfort with retrieval pipelines, vector stores, and structured memory for agentsKubernetes and containerized deployment fluencyGenuine interest in offensive security and the ability to ramp quickly on OWASP Top 10, API security, web app pentesting, and mobile pentesting concepts. Direct offensive security background is a strong plus but not requiredOffensive security background: OSCP/OSWE/OSWA, CTF, bug bounty, or prior red team workResearch publications at NeurIPS, ICML, ICLR, USENIX Security, IEEE S&P, Black Hat, or DEFCONOpen source contributions to agent frameworks or LLM toolingExperience with adversarial ML or red-teaming AI systemsFamiliarity with mobile app reverse engineering or binary analysisCompany OverviewAssail develops an agentic AI platform for autonomous offensive security testing targeting mobile apps, APIs, and web infrastructure. It was founded in 2025, and is headquartered in Boston, Massachusetts, USA, with a workforce of 2-10 employees. Its website is https://www.assailai.com.