Machine Learning Engineer

About The Company

LexisNexis is a renowned global provider of legal, regulatory, and business information and analytics. With a rich history of innovation, LexisNexis has been at the forefront of transforming complex data into accessible insights that drive smarter decision-making and improved outcomes. The company’s mission is to help professionals increase productivity, ensure compliance, and uphold the rule of law worldwide. As a pioneer in digital information services, LexisNexis was the first to bring legal and business information online through its flagship Lexis and Nexis platforms, establishing itself as a trusted name in the industry. Committed to excellence and integrity, LexisNexis continually evolves its offerings to meet the dynamic needs of its diverse client base, ranging from legal professionals and government agencies to corporations and academic institutions.

About The Role

We are seeking a highly skilled and motivated Principal AI Engineer to join our team, focusing on architecture and solution development within the AI domain. This role is designed for an experienced AI developer or technical lead who possesses strong engineering expertise, a deep understanding of modern AI architectures, and a passion for creating scalable, secure, and innovative AI solutions. The Principal AI Engineer will collaborate closely with product managers, data scientists, software engineers, security teams, and government stakeholders to translate complex business and mission requirements into robust AI capabilities. Initially, the role emphasizes hands-on solution design and implementation, but it also offers opportunities to grow into a broader AI architecture leadership position, shaping technical standards, governance policies, and cross-team strategies. This position plays a critical role in modernizing legacy workflows, leveraging automation, artificial intelligence, and platform transformation to enhance efficiency, accuracy, and cost-effectiveness in highly regulated environments.

Qualifications

The ideal candidate will possess a combination of educational background and practical experience, including:

• A 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 delivering production applications or platforms.
• Hands-on experience developing AI, machine learning, or data-intensive solutions.
• Proficiency in Python, with experience in APIs, cloud services, data pipelines, source control, and software development best practices.
• Experience with modern generative AI patterns such as large language models, retrieval-augmented generation, embeddings, vector search, AI agents, and tool integration.
• Understanding of cloud-native architecture, system integration, identity and access management, observability, and secure development practices.
• Ability to evaluate and explain technical alternatives, architecture decisions, and tradeoffs effectively.
• Experience working collaboratively across product, engineering, data, security, and business teams.
• Strong written and verbal communication skills, with the ability to convey complex AI concepts clearly to diverse audiences.
• Eligibility to satisfy government background checks and security clearance requirements.
• Knowledge of security, privacy, accessibility, explainability, and human oversight principles in AI solutions.

Preferred qualifications include experience with government contracting, cloud platforms (AWS, Azure, Google Cloud), AI orchestration frameworks, model evaluation, and leadership in technical reviews or mentoring roles. Certifications in cloud, security, or AI are also advantageous.

Responsibilities

The successful candidate will undertake a variety of technical and collaborative responsibilities, including:

AI Solution Design and Development

• Design, prototype, and implement AI-powered applications, services, agents, and workflows aligned with mission and business needs.
• Translate complex requirements into practical, scalable technical solutions using large language models, NLP, computer vision, and other AI technologies.
• Develop reusable AI components, APIs, evaluation frameworks, and reference implementations.
• Integrate AI capabilities seamlessly with enterprise platforms, data sources, and existing applications.
• Balance rapid experimentation with engineering discipline to ensure secure, reliable production systems.
• Evaluate models, platforms, and vendors based on performance, cost, security, and mission suitability.

Architecture and Technical Leadership

• Contribute to comprehensive solution architectures covering applications, data, models, integrations, and infrastructure.
• Partner with senior architects to establish AI architecture standards, guardrails, and reference models.
• Assist teams in making informed decisions regarding AI capabilities, tools, and frameworks.
• Identify opportunities for shared AI services, reusable components, and cross-platform capabilities.
• Participate in architecture reviews, documenting decisions, tradeoffs, risks, and assumptions clearly.
• Provide technical guidance, code reviews, mentoring, and support to engineering and data science teams.
• Advance towards ownership of end-to-end AI solution architecture and broader technical strategy.

Government and Stakeholder Engagement

• Support technical discovery sessions, demonstrations, proofs of concept, and proposal development.
• Communicate complex AI concepts, limitations, risks, and tradeoffs effectively to both technical and non-technical audiences.
• Facilitate transitioning successful prototypes into secure, scalable, and operational production systems.
• Stay informed about evolving government policies, standards, and responsible AI practices.

Benefits

We are committed to supporting our employees' well-being and professional growth. Our benefits package includes:

Comprehensive health benefits covering medical, dental, and vision