Senior Cloud and AI Security Engineer
About the job
- Experience in machine learning engineering and strong experience in cloud security engineering, application security, security architecture, DevSecOps, or security automation.
- Hands-on experience with at least one major cloud platform such as AWS or Azure.
- Practical knowledge of identity and access management, logging, encryption, secrets management, network security, storage security, vulnerability management, and secure continuous integration and continuous delivery.
- Experience with infrastructure as code and cloud security tooling such as cloud security posture management, cloud-native application protection platforms, infrastructure-as-code scanning, static application security testing, software composition analysis, secrets scanning, or policy as code.
- Ability to translate security standards and architecture requirements into practical implementation patterns.
- Familiarity with generative artificial intelligence, large language model-enabled applications, artificial-intelligence-assisted development, or artificial intelligence security risks.
- Strong scripting, automation, workflow design, or tooling integration experience.
- Excellent written and verbal communication skills, with the ability to create clear security guidance for engineering teams.
- Build and maintain reusable cloud security guardrails for identity, logging, encryption, network segmentation, secrets management, storage, workloads, containers, serverless services, and data protection.
- Translate security architecture standards into deployable cloud patterns, reference implementations, templates, and engineering-ready requirements.
- Partner with cloud, platform, DevOps, and product engineering teams to embed security controls into cloud landing zones, continuous integration and continuous delivery pipelines, infrastructure-as-code workflows, and operational processes.
- Support the implementation and tuning of cloud security posture management, cloud-native application protection platforms, cloud workload protection, infrastructure-as-code scanning, secrets scanning, and related cloud security tooling.
- Develop policy-as-code and control-as-code mechanisms to prevent, detect, and report common cloud misconfigurations.
- Support cloud-native vulnerability and misconfiguration remediation by providing prioritization logic, remediation guidance, and reusable fix patterns.
- Establish cloud security metrics and dashboards covering control adoption, misconfiguration trends, remediation progress, recurring issues, and exception patterns.
- Design and maintain AI-assisted workflows for security intake triage, threat model drafting, architecture review summaries, control mapping, remediation guidance, and risk statement generation.
- Build prompt libraries, review rubrics, validation steps, and human-in-the-loop processes for approved AI use within Information Security.
- Identify repetitive BISO, application security, and Security Architecture tasks that can be safely accelerated through AI-assisted processes.
- Partner with GRC, Legal, Privacy, and security leadership to ensure AI-assisted security workflows are auditable, explainable, and aligned with internal risk expectations.
- Measure the effectiveness of AI-assisted workflows, including time saved, consistency improvements, review quality, and reduction in repeat manual work.
- Define secure design patterns for AI-enabled applications, including large-language-model-based features, retrieval-augmented generation, AI agents, AI APIs, copilots, and automation workflows.
- Establish cloud security requirements for AI workloads, including identity, secrets, data storage, network access, observability, workload isolation, and third-party AI service integrations in partnership with Security Architecture and application security.
- Support AI application threat modelling and risk reviews in partnership with BISO and application security.
- Create developer-facing guidance for safe use of AI coding assistants, AI APIs, data ingestion, vector stores, model outputs, and AI-generated code in partnership with BISO and application security.
- Convert recurring BISO, application security, and Security Architecture questions into reusable guidance, decision trees, approved patterns, checklists, and self-service workflows.
- Build lightweight intake and routing mechanisms that determine when a request needs BISO review, application security review, architecture review, GRC input, or engineering remediation.
- Create and maintain a library of approved cloud and AI security patterns that product and engineering teams can reuse.
- Help reduce one-off security consultations by embedding approved security decisions into tooling, templates, and standard delivery workflows.
- Experience building cloud security guardrails, landing zone controls, reusable modules, or automated remediation workflows.
- Experience supporting regulated environments or environments with strict customer, contractual, or compliance obligations.
- Familiarity with AI security frameworks and guidance such as the NIST AI Risk Management Framework, NIST Generative AI Profile, OWASP Top 10 for LLM Applications, or Cloud Security Alliance AI security guidance.
- Experience with retrieval-augmented generation architecture, AI agents, vector databases, AI APIs, prompt engineering, or AI application threat modelling.
- Experience building security knowledge assistants, prompt libraries, AI-assisted review workflows, or security automation.
About the company
LexisNexis Risk Solutions provides data, analytics, and decision tools to help organizations assess and manage risk across many industries. Its offerings combine large data sets with advanced analytics to support better decisions, improve operations, and protect consumers. By covering sectors like financial services, government, healthcare, insurance, retail, and public safety, the company helps customers evaluate likelihoods of risk, detect issues, and act more efficiently. The goal is to turn data into actionable insight that reduces risk, increases operational efficiency, and supports compliant, informed decision-making for its clients.
Company Size
5,001-10,000
Company Stage
N/A
Total Funding
N/A
Headquarters
Alpharetta, Georgia
Founded
1997
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Simplify's Take
What believers are saying
- Arizona's Digital Birth Credential rollout expanded statewide June 1, 2026.
- Cytora, Epic, and Agenium integrations widen distribution across commercial, healthcare, and life insurance.
- 2026 reports show rising fraud, higher home severity, and SNAP losses $4.29 per dollar.
What critics are saying
- Choksi v. LexisNexis Risk Solutions and Ioane v. LexisNexis Risk Solutions expand FCRA exposure.
- Scroggins settled for $13.5 million after false deceased reports; data quality remains a liability.
- TransUnion, Experian Health, and Socure target adjacent identity and fraud budgets aggressively.
What makes LexisNexis Risk Solutions unique
- RELX-backed LexisNexis Risk Solutions spans fraud, insurance, healthcare, and government workflows.
- Emailage Adaptive, launched October 1, 2026, self-calibrates and cuts false positives 80%.
- FedRAMP In Process status and TxRAMP certification strengthen public-sector trust.
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Benefits
Health Insurance
401(k) Company Match
Wellness Program
Short-and-Long Term Disability
Life Insurance
Family Planning Benefits
Health Savings Account/Flexible Spending Account
Paid Vacation
Company News
LexisNexis Risk Solutions has launched Emailage Adaptive, a self-calibrating AI fraud detection solution that continuously learns from each organisation's unique fraud patterns without manual intervention. In testing, the system captured around 90% of frauds amongst highest-risk transactions while reducing false positives by more than 80%. Dell Technologies has doubled its high-risk fraud capture rates and reduced manual reviews of low-risk transactions by 83% since implementing the solution. The launch addresses rising fraud costs, with one in every 11 new account creations globally being fraudulent attempts, according to LexisNexis's Cybercrime Report 2026. The solution analyses email, IP, phone and address signals whilst providing transparent scoring with clear reason codes for each risk assessment.
LexisNexis Risk Solutions and IMS have integrated the LexisNexis Drive Metrics scoring model into the IMS EdgeSDK to create a smartphone-based telematics solution for US auto insurers. The integration enables insurers to launch or improve usage-based insurance programmes whilst reducing costs by 50% or more by eliminating cloud processing and storage fees. The solution keeps driving behaviour data on users' devices whilst generating scores that can be incorporated into existing workflows. It can be embedded into insurance company apps or utilised through an IMS white-label app. The LexisNexis Drive Metrics model has demonstrated 79% improvement above standard rating factors. The partnership aims to make telematics intelligence accessible to insurers of all sizes, providing more personalised pricing for consumers whilst maintaining data privacy and transparency.
Arizona has launched the nation's first Digital Birth Credential in collaboration with LexisNexis Risk Solutions and state agencies. The programme allows Arizona-born residents to access a verified digital version of their birth certificate on their mobile devices. Residents can present the credential from their smartphones when applying for services at Arizona Department of Transportation Motor Vehicle Division offices. The initiative aims to reduce reliance on paper documents whilst lowering risks of document loss, theft, and identity fraud. The programme initially launched at three MVD pilot locations in November 2025 before expanding statewide on 1 June 2026. It leverages LexisNexis VitalChek technology to streamline workflows and enhance fraud prevention, establishing a model for digital government transformation nationwide.
LexisNexis Risk Solutions has launched Location Intelligence for Home, an AI-driven predictive model for US home insurance carriers to assess property risk. The tool uses neural network modelling and industry-wide claims data to evaluate six perils, including hail, wind and non-weather water damage. Properties with the highest Location Intelligence scores are 20 times more likely to have a claim than those with the lowest scores. The system addresses gaps in traditional assessment methods, particularly important as non-weather water claims represented 24% of all claims in 2025. The solution integrates within LexisNexis Smart Selection, enabling underwriters to apply location-based insights consistently across new business and renewals. The company plans to file the model in various US states for underwriting and rating workflows.
Cytora and LexisNexis Risk Solutions have announced a strategic partnership to enhance digital risk processing for US commercial insurers by integrating LexisNexis data and analytics into Cytora's AI-powered underwriting platform. The collaboration allows commercial insurers to automatically enrich submissions with external information, reducing manual lookups and accelerating risk decisioning. Cytora's platform digitises incoming risks and augments them with external data sources, whilst LexisNexis provides industry-leading data analytics and proprietary linking technology for business entity resolution. The integration begins with US commercial business firmographics data via LexisNexis Commercial Data Prefill, with additional LexisNexis commercial insurance products to follow. The partnership aims to transform underwriting from a reactive process into a proactive, insight-driven discipline whilst streamlining critical processes across the entire policy lifecycle.