Principal Machine Learning Engineer * Hybrid in Horsham, PA or Remote EST

About Our Team

For over 50 years, Lexis Nexis Reed Technology has partnered with the U.S. Patent and Trademark Office (USPTO) to deliver secure, scalable, and high-quality patent data processing solutions. Our work transforms complex, unstructured patent submissions into standardized, searchable outputs that power examiner workflows and public dissemination. We operate in a highly regulated environment with strict security requirements, large-scale data volumes, and complex business rules.

Our focus is on modernizing legacy workflows through automation, AI, and platform transformation to improve efficiency, accuracy, and cost effectiveness.

Principal AI Engineer – Architecture Track

We are seeking a hands‑on Principal AI Engineer who can design and build production‑grade AI solutions while growing into a broader AI Architect role. This position is ideal for an experienced AI developer or technical lead who has strong engineering depth, understands modern AI architecture, and is ready to expand their influence across platforms, products, and delivery teams. The Principal AI Engineer will work closely with product managers, architects, data scientists, software engineers, security teams, and government stakeholders to translate mission and business needs into secure, scalable, and reusable AI capabilities.

The role will initially focus on solution design and hands‑on implementation, with increasing responsibility for architecture standards, technical strategy, governance, and cross‑team alignment.

*** Conditions of Employment:

You must be a U.S. citizen to apply for this position. You must successfully pass a background investigation and achieve Public Trust security clearance. Must be located near the Horsham, PA location for a hybrid onsite schedule.

• AI Solution Design and Development
  • Design, prototype, and implement AI‑powered applications, services, agents, and workflows.
  • Translate business, user, and government mission requirements into practical technical solutions.
  • Develop solutions using large language models, retrieval‑augmented generation, machine learning, natural language processing, computer vision, or other relevant AI technologies.
  • Build reusable AI components, services, APIs, evaluation frameworks, and reference implementations.
  • Integrate AI capabilities with enterprise platforms, data sources, workflows, and existing applications.
  • Balance rapid experimentation with the engineering discipline required for secure, reliable production systems.
  • Evaluate models, platforms, frameworks, and vendors based on performance, cost, security, scalability, and mission fit.
• Architecture and Technical Leadership
  • Contribute to solution architectures covering applications, models, data, integrations, infrastructure, security, and operational monitoring.
  • Partner with senior architects to establish AI architecture patterns, guardrails, standards, and reference architectures.
  • Help teams make informed decisions regarding commercial, open‑source, and internally developed AI capabilities.
  • Identify opportunities to create shared AI services and reusable capabilities across products, contracts, and government agencies.
  • Participate in architecture reviews and clearly document technical decisions, tradeoffs, assumptions, and risks.
  • Provide technical guidance, code reviews, mentoring, and hands‑on support to engineering and data science teams.
  • Grow into ownership of end‑to‑end AI solution architecture and broader technical strategy.
• Government and Stakeholder Engagement
  • Support technical discovery sessions, demonstrations, proofs of concept, proposals, RFIs, and RFP responses.
  • Communicate complex AI concepts, limitations, risks, and tradeoffs clearly to both technical and non‑technical…