Jobs at Skyfall AI

Conduct research to advance agentic systems by developing methods for planning, reasoning, and reinforcement learning with LLMs and multi-agent systems. Design experiments, build datasets, and stay current with academic advances to improve LLM performance in complex workflows.

Manage LLM-focused research projects: translate research goals into roadmaps, coordinate PhD researchers and research engineers, oversee data curation, experiment protocols, benchmarking, budgets, risk mitigation, documentation, and external academic/industry collaborations to drive publications and product integration.

Lead and manage a research team developing agentic AI, focusing on reinforcement learning, transformer‑based generative models (LLMs, diffusion), and multi‑agent systems. Define research strategy, keep pace with state of the art, and build external academic and community relationships to position Skyfall as an AI leader.

Develop tools and infrastructure for training language models in interactive environments, implement novel methods in language modeling, reinforcement learning and multi-agent systems, and contribute to publications and open-source projects.

Lead product vision, strategy, and execution for a chat-first enterprise platform. Collaborate with data scientists, ML engineers, and designers to build conversational AI features, curate datasets, implement benchmarking and training workflows, define KPIs, and drive data-driven product optimization for enterprise workflow automation.

Lead and mentor a research team developing agentic AI (planning, RL, LLMs, diffusion, multi-agent systems). Define and execute research strategy, track state-of-the-art work, and build external AI community relationships to position Skyfall as a research leader.

Drive research and development of large language models: pre-training, fine-tuning, RLHF, instruction tuning, and prompt engineering. Optimize LLMs for domain-specific tasks, explore novel architectures and training methods, and integrate research advances into production-grade enterprise solutions.

Lead end-to-end product strategy and roadmap for enterprise IT solutions (ITSM, ITAM, ITOM). Gather technical requirements, define integrations with ServiceNow/Atlassian/BMC, oversee API and data pipeline development, and ensure interoperability and compliance with ITIL and enterprise standards.

Manage and coordinate LLM-focused research projects: translate research goals into multi‑phase roadmaps, track milestones, oversee data curation and experiments, coordinate PhD researchers and research SDEs, manage budgets and risks, document results, and support publications and external academic or industry collaborations.

Build tools and infrastructure for training language and multi-agent models in interactive environments; research and implement advances in language modeling and reinforcement learning; contribute to publications and open-source projects.

Conduct research to advance agentic systems by developing methods for planning, reasoning, and reinforcement learning with LLMs and multi-agent systems; build experiments and datasets to improve LLM performance in complex workflows; stay current with academic advances.