Principal Machine Learning Engineer I** Hybrid in Horsham, PA or Remote EST Preferred
AI in this role
About Our Team
For over 50 years, LexisNexis 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.
About the Role
Principal AI Engineer – Architecture TrackWe 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.
Responsibilities
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 audiences.
- Help move successful prototypes into secure, supportable, and scalable production capabilities.
- Stay informed about evolving government AI policies, standards, acquisition practices, and responsible-AI expectations.
Requirement
- Bachelor’s degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience.
- Significant professional software engineering experience, including experience delivering production applications or platforms.
- Hands-on experience developing AI, machine-learning, or data-intensive solutions.
- Proficiency in Python and experience with APIs, cloud services, data pipelines, software development practices, and source control.
- Experience with modern generative-AI patterns, such as large language models, retrieval-augmented generation, embeddings, vector search, tool use, structured outputs, or AI agents.
- Understanding of cloud-native architecture, system integration, identity and access management, observability, and secure development practices.
- Ability to evaluate technical alternatives and explain architecture decisions and tradeoffs.
- Experience working across product, engineering, data, security, and business teams.
- Strong written and verbal communication skills.
- Ability to satisfy applicable government background, suitability, or contractual requirements.
- Incorporate security, privacy, accessibility, explainability, auditability, and human oversight into solution designs.
- Establish appropriate evaluation methods for accuracy, relevance, groundedness, bias, safety, and reliability.
- Design controls for model and prompt versioning, data lineage, access management, logging, monitoring, and traceability.
- Partner with cybersecurity, legal, privacy, compliance, and governance teams throughout the solution lifecycle.
- Ensure solutions align with applicable organizational policies, contractual obligations, and government requirements.
- Design human-in-the-loop controls based on the risk and impact of the decisions supported or performed by AI.
Preferred Qualifications
- Experience delivering technology solutions for U.S. federal, state, or local government customers.
- Experience working in government contracting, regulated environments, or programs involving sensitive data.
- Familiarity with government security and compliance frameworks, such as NIST, FedRAMP, FISMA, or agency-specific controls.
- Experience with one or more major cloud platforms, particularly AWS, Microsoft Azure, or Google Cloud.
- Experience with AI orchestration frameworks, model gateways, vector databases, evaluation platforms, MLOps, or LLMOps.
- Understanding of model evaluation, prompt engineering, fine-tuning, data governance, and responsible-AI practices.
- Experience moving AI proofs of concept into production.
- Experience supporting technical proposals, RFIs, RFPs, solution demonstrations, or customer workshops.
- Prior technical leadership, mentoring, or architecture-review experience.
- Relevant cloud, architecture, security, data, or AI certifications.
Work in a Way That Works for You
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working flexible hours to help you fit everything in and work when you are the most productive
Working for You
We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs
Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits
Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice
About the Business
LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services.


U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates.



This job is eligible for an annual incentive bonus.





We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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How we rate this
Principal Machine Learning Engineer I** Hybrid in Horsham, PA or Remote EST Preferred at RELX rates 68 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you monitor a model once it's live, and how do you know it needs retraining?
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, RAG, AI Agents, Fine Tuning, and ML Ops. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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