Head of Applied AI for Tax & Accounting Workflows

PowerToFly

United States

Remote

USD 198,000 - 368,000

Full time

14 days+

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Job summary

Thomson Reuters Labs seeks an experienced applied science leader to guide a high‑performing team building agentic AI solutions for tax and accounting professionals worldwide. You will partner with product, engineering and domain experts to bring research into scalable, production‑grade capabilities, ensuring accuracy and trust in high-stakes environments.

Ideal candidates combine deep AI expertise with a strong product mindset, hands-on experience with LLMs, and a track record of delivering

Qualifications

PhD in Computer Science, Machine Learning, or a closely related field; or a Master's degree with equivalent depth, a strong scientific background, and a relevant publication record.
10+ years of hand‑on industry experience building AI and machine learning systems for commercial applications; research‑only experience is not sufficient.
Recent, direct hand‑on experience developing LLM‑based and agentic AI systems for production, non‑trivial use cases.
5+ years of experience managing and developing high‑performing applied science, machine learning, or AI research teams.
Demonstrated success in product‑facing or customer‑facing roles, with measurable business and customer impact as the primary measure of success.
Technical depth in AI and machine learning sufficient to challenge assumptions, expand upon team ideas, guide high‑quality technical decisions, and establish effective research direction.
Strong expertise in information retrieval and natural language processing, particularly in complex vertical domains.
Experience with taxonomy induction, document understanding, agentic search, knowledge graphs, neuro‑symbolic AI, or comparable approaches for complex knowledge‑intensive workflows.
Experience evaluating AI agents and language‑model‑based systems, including approaches involving verifiable rewards, synthetic data generation, and rigorous quality measurement.
A relevant publication record, including publications at ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, KDD, or equivalent venues.
Experience building AI solutions for tax, legal, audit, accounting, or other highly regulated and knowledge‑intensive domains.
A demonstrated track record of growth and leadership at top‑tier technology companies, high‑growth startups, or similarly demanding environments.
Strong communication and influencing skills, with the ability to work effectively with applied scientists, engineers, product leaders, domain experts, and senior business stakeholders.
A passion for developing people, building strong teams, and creating an inclusive, high‑performing culture.

Responsibilities

Lead and develop a high-performing applied science team focused on agentic AI solutions for tax and accounting professionals.
Drive the design, development, and delivery of AI features that meaningfully reimagine customer workflows in high-stakes, accuracy-critical settings.
Set technical direction for applied research initiatives, balancing scientific rigor, customer value, product feasibility, and delivery timelines.
Partner closely with product engineering teams to transition research innovations into scalable, reliable, production-ready capabilities.
Serve as a strategic thought partner to Labs leadership, product leadership, and key business stakeholders on long-term AI strategy, external partnerships, and capability roadmaps.
Influence product strategy through deep technical expertise and insights derived from product usage data, quality metrics, evaluations, and customer feedback.
Develop and advance approaches for LLM-based systems, agentic workflows, information retrieval, document understanding, knowledge representation, and AI evaluation.
Ensure AI systems are designed with appropriate accuracy, verification, observability, safety, and quality controls for professional tax and accounting use cases.
Engage tax, audit, accounting, and other subject‑matter experts in concept development, design workshops, experimentation, and solution validation.
Continuously improve ways of working across R&D and product engineering in a fast‑paced, tightly embedded delivery environment.
Foster a culture of innovation, rigor, collaboration, technical excellence, and continuous learning across the team.
Represent TR Labs and the broader tax technology organization in internal technical forums, cross‑functional initiatives, and relevant external research communities.