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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Machine Learning Engineer I** Hybrid in Horsham, PA or Remote EST Preferred - **Company:** LexisNexis - **Location:** Raleigh, NC, United States - **Salary:** $136,100.0 - $252,800.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Computer Vision, Microsoft Azure, Cloud Computing, Cloud Engineering, Code Review, Information Systems, Data Governance, Identity and Access Management, Python (Programming Language), Machine Learning, Natural Language Processing, Open Source Technology, Cloud Services, Search Technologies, Secure Coding, Software Engineering, Systems Integration, Management of Software Versions, Lexis, Data Logging, Data Processing, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, IT Architecture, Model Validation, Generative AI, Agentic-AI, AI Platforms, Information Technology, Data Lineage, Machine Learning Operations, Multiplatform, Software Version Control, Data Pipelines - **Published:** October 27, 2026 - **Apply:** https://www.careerbuilder.com/job-details/principal-machine-learning-engineer-i-hybrid-in-horsham-pa-or-remote-est-preferred-raleigh-nc--877ca916-183e-4b81-8632-c2536561bb8d ## About the Role Machine Learning, US Patent and Trademark Offices, Patents, LexisNexis, Data Processing, Automation, Cost Effectiveness Analysis, Artificial Intelligence (AI), Technical Leadership, Multiplatform/Cross-Platform, * 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., * 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. ## Description 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., 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.