Principal AI Researcher – Agentic Systems, AI Infrastructure

Trase

Principal AI Researcher defining and driving research for Trase's AI operating system. Focusing on autonomous systems in regulated environments with hands-on technical leadership.

Posted 5/21/2026full-timeRemote • Virginia, Washington • 🇺🇸 United StatesLead💰 $250,000 - $300,000 per yearWebsite

Tech Stack

Tools & technologies

CloudJavaPython

About the role

Key responsibilities & impact

Define and evolve the long-term AI/ML research strategy and technical roadmap for Trase OS in alignment with product and platform direction.
Lead large-scale experimentation and prototyping efforts requiring significant compute infrastructure, translating frontier AI research into scalable, production-grade systems with measurable impact.
Drive original research and technical breakthroughs in agentic systems, autonomous execution, multi-agent orchestration, post-training and fine-tuning systems, SLM/LLM-based architectures, and applied AI infrastructure.
Design how models operate within long-lived execution environments, including agent workflows, tool use, planning, memory systems, reasoning, and human-in-the-loop controls.
Establish evaluation methodologies and reliability frameworks for autonomous systems, including benchmarking, regression testing, safety, controllability, and production behavior analysis.
Drive architecture decisions across orchestration, model serving, routing, inference, and infrastructure governance, including latency, reliability, and cost optimization.
Partner closely with engineering and product teams to operationalize research outcomes into deployable systems and enterprise workflows.
Build AI systems that operate reliably in regulated and constrained environments, including secure cloud, on-premise, and air-gapped deployments.
Contribute to the broader AI research community through technical papers, publications, conference participation, architecture proposals, and thought leadership.
Serve as a senior technical authority and mentor across the organization, influencing technical direction, research rigor, experimentation practices, and best practices across research, engineering, and product teams.

Requirements

What you’ll need

12–15+ years of experience in machine learning, AI systems, or applied AI research, including experience operating at a Principal, Distinguished, or equivalent technical level.
Strong research and publication track record, including authored papers, major technical contributions, or active participation in frontier AI research.
Experience publishing at top-tier conferences or contributing influential open-source, research, or AI infrastructure systems.
Experience conducting large-scale experimentation requiring significant compute infrastructure, evaluation workflows, and iterative model/system analysis.
Deep expertise in one or more areas including agentic systems, LLMs and generative AI, multi-agent systems, reasoning systems, reinforcement learning, orchestration infrastructure, AI systems reliability, NLP, multimodal systems, or deep learning.
Hands-on experience with agent-based systems, prompt engineering, RAG, RLHF, SLMs, fine-tuning/post-training techniques, tool integration, memory systems, and human-in-the-loop orchestration.
Proven experience building, deploying, and operating enterprise-grade AI systems, including GenAI, LLM, or agent-based applications at scale.
Strong understanding of ML system behavior in production, including reliability, latency, cost tradeoffs, observability, evaluation frameworks, regression testing, and failure modes.
Strong systems thinking and demonstrated ability to partner cross-functionally with engineering and product organizations to move research into production systems.
Strong programming and prototyping skills in Python and modern ML infrastructure stacks, with experience in Java or related systems languages preferred.
Experience deploying AI/ML systems in regulated, constrained, or enterprise environments, and demonstrated ability to lead technical direction from research through production impact.

Benefits

Comp & perks

Career track opportunity with potential for rapid advancement with strong performance as the firm grows
100% employer paid, comprehensive health care including medical, dental, and vision for you and your family.
Paid maternity and paternity for 14 weeks at employees' normal pay.
Unlimited PTO, with management approval.
Opportunities for professional development and continued learning.
Optional 401K, FSA, and equity incentives available.
Mental health benefits are available through Tara Mind.

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Hard Skills & Tools

machine learningAI systemsapplied AI researchagentic systemsLLMsgenerative AImulti-agent systemsreinforcement learningdeep learningPython

Soft Skills

systems thinkingcross-functional collaborationmentorshiptechnical authorityresearch rigorexperimentation practicesinfluencing technical directioncommunicationleadershipproblem-solving