Sr Consulting/Principal Software Engineer

Are you passionate about building secure, scalable technology solutions and leading innovation across AI, cloud, and enterprise infrastructure?

Do you enjoy mentoring engineers, shaping technical standards, and solving complex business challenges through modern engineering practices?

About the Business

LexisNexis® Risk Solutions provides customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. We use the power of data and advanced analytics to help our customers make better, timelier decisions. By bringing clarity to information, we ultimately help make communities safer, insurance rates more accurate, commerce more transparent, business decisions easier and processes more efficient. You can learn more about LexisNexis Risk at 

https://risk.lexisnexis.com/

About our Team

ACE (AI & Core Engineering) is a shared services technology organization within LexisNexis Risk Solutions focused on building the foundational engineering platforms, cloud capabilities, and applied AI solutions that power the company’s risk, identity, fraud, and data-driven products. The team combines core software engineering, cloud architecture, and AI/ML enablement to deliver scalable, secure, and reliable capabilities used across product lines, helping teams move faster while maintaining enterprise-grade quality, governance, and operational excellence.

About the Role:

This position is a subject matter expert on broad technologies and sets the architectural standard for the workgroup. The position executes corporate tactical technology strategy on large multifunctional development activities, solves complex technical problems, writes complex code for computer systems, and serves as a senior source of expertise. This position is expected to be seen as a “go to” person across the division for a set of technologies.

RESPONSIBILITIES:

CORE ENGINEERING SKILLS:

• Industrywide or broad companywide technical knowledge across large, complex systems.

• Expertise in development languages; proficient in reading, writing, reviewing, and generating code across most modern languages.

• Software development process expert in applicable methodologies, practices, and emerging trends.

• Strong knowledge of architectural principles and proven application of industry best practices across all aspects of development.

• Expertise in test-driven development, automated testing, and maintenance techniques applied for overall project benefit.

• Expertise in data modeling (normalized/dimensional), data manipulation languages, optimization, tuning, and best practices.

• Expert knowledge of multiple data storage subsystems and complex data models.

• Knowledge of domain specific languages and their application.

• Ability to write and review detailed specifications for system components of advanced complexity.

AI SOFTWARE ENGINEERING SKILLS:

• Ability to spot AI hallucination in results and apply techniques to remove them

• Specialized coding skills with an emphasis on high-quality, review-ready AI code generation and human-in-the-loop validation.

• Ability to prompt and orchestrate all forms of AI-assisted work tools, including enterprise tools such as M365 Copilot, Copilot Studio, Cowork, Enterprise ChatGPT, GitHub Copilot, Claude Code, and other modern AI harnesses.

• Ability to write effective markdown, instructions, and agent/skill definitions to support prompting, MCP (Model Context Protocol) integration, workflow automation, code generation, and spec-driven development.

• Experience with spec-driven and context-driven development: authoring requirements, specs, and evals that AI agents can execute reliably.

• Ability to design, build, and integrate AI agents and multi-agent workflows, including tool/function calling, retrieval-augmented generation (RAG), and MCP servers/clients.

• Understanding of LLM application patterns: prompt engineering, context management, embeddings/vector stores, evaluation, guardrails, and cost/latency/token optimization.

• Ability to evaluate AI-generated output for correctness, security, and maintainability, and to establish team standards for responsible, secure AI-assisted SDLC practices.

• Awareness of AI safety, data governance, and privacy considerations (e.g., PII handling, model/data provenance) in AI-assisted engineering workflows.

SECURITY SKILLS:

• Security expert across domains, security champion.

• Cloud and infrastructure security fundamentals: identity and access management, secrets management, network segmentation, and least-privilege design.

• Deep understanding of direct and indirect prompt injection, model poisoning, confused deputy, and other emerging AI threats.

• Understanding of the principles in OWASP, NIST, ISO, and other international security standards.

• Ability to spot insecure code and remediate it quickly and completely.

• Participation in red team activities or similar tactical security drills.

• Can run security sweeps and bug bounty programs.

INFRASTRUCTURE, CLOUD & SRE SKILLS

• Strong experience designing, deploying, and operating workloads across multiple cloud providers (e.g., AWS, Azure, GCP) with an understanding of trade-offs in a multi-cloud/hybrid strategy.

• Infrastructure-as-Code expertise (e.g., Terraform, Bicep/ARM, CloudFormation, Pulumi) and configuration management (e.g., Ansible).

• Containerization and orchestration expertise (Docker, Kubernetes) including Helm, service mesh, and workload scaling patterns.

• CI/CD pipeline design and automation (e.g., GitHub Actions, GitLab CI, Azure DevOps) supporting reliable, repeatable delivery.

• Site Reliability Engineering practices: SLOs/SLIs/error budgets, observability (metrics, logs, traces), monitoring/alerting, incident response, and blameless postmortems.

• Resilience engineering: capacity planning, autoscaling, high availability, disaster recovery, and cost optimization (FinOps) across cloud environments.

ON-PREMISE SYSTEMS & NETWORK ENGINEERING SKILLS

• Systems engineering across Linux and Windows Server environments, including provisioning, hardening, patching, and lifecycle management.

• On-premise and hybrid infrastructure skills: virtualization (e.g., VMware, Hyper-V), bare-metal servers, storage (SAN/NAS), and backup/recovery.

• Network engineering fundamentals: TCP/IP, DNS, DHCP, VLANs, routing/switching, load balancing, firewalls, VPNs, and network troubleshooting.

• Datacenter operations experience, including capacity, power/cooling awareness, and coordination of on-prem-to-cloud connectivity (e.g., Direct Connect, ExpressRoute, VPN gateways).

• Ability to design and support hybrid architectures that bridge on-premise infrastructure with multi-cloud services securely and reliably.

DELIVERY & RESOURCE MANAGEMENT SKILLS

• Proven expert in partnering with and leading internal and external technology resources to solve complex business needs.

• Strong experience with various resource models such as Managed Services and/or Staff Augmentation.

• Strong organization, project planning, time management, and change management skills, including prioritizing and reprioritizing work across projects of varying size and complexity.

• Budgeting and finance awareness in support of technology decisions.

• Proven ability to adapt to new roles and responsibilities.

SOFT SKILLS

• Curiosity and continuous learning — an intrinsic drive to explore new technologies, ask good questions, and stay current with fast-moving industry and AI trends.

• Reading and research — strong ability to rapidly read, comprehend, and synthesize documentation, code, specs, and research to inform sound technical decisions.

• Writing — clear, concise, and effective written communication, including specifications, documentation, and AI prompts/instructions.

• Verbal communication — articulate and precise in discussions with peers, stakeholders, and leadership.

• Presentation — able to present complex technical information concisely and persuasively to audiences ranging from engineers to senior and executive management.

• Small-team efficiency — thrives in lean, high-trust teams; self-directed, collaborative, and able to deliver outsized impact with minimal overhead.

• Advanced problem-solving — identifies, researches, and coordinates the resources needed to diagnose complex issues, translate findings into solutions, and surface risks and trade-offs for decision-making.

ACCOUNTABILITIES

• Perform reviews to ensure enterprise and architectural standards and processes are followed.

• Build smart and scalable computer systems and serve as a senior source of expertise.

• Manage system and user acceptance testing cycles to ensure accurate and quality business solutions.

• Lead the development of technical standards, and perform reviews to ensure enterprise and architectural standards and processes are followed.

• Serve as a primary technical point of contact for external technology resources.

• Act as a technology mentor to other engineers.

• Recommend technical strategy and direction across functional area.

• Participate in development and evolution of architecture.

• Consult with stakeholders to find alternative work-arounds during system outages.

• Provide design input across a product.

• Work directly with customers and end users.

• Serve as acknowledged “go to” person on AI software engineering and technical issues.

• Establish standards and guardrails for responsible, secure AI-assisted development and mentor the team on AI SDLC practices.

• Design and operate reliable infrastructure across multi-cloud and on-premise/hybrid environments, applying SRE practices to meet availability and performance objectives.

• Interface with other technical personnel or team members to finalize requirements.

• Write and review portions of detailed specifications for the development of system components of moderate complexity.

• Complete complex bug fixes.

• Design and work with complex data models.

• Mentor lead software developers on consultancy path on development methodologies and optimization techniques.

• Seek diverse ideas and perspectives from a variety of sources to create better solutions, products, and services.

U.S. National Base Pay Range: $118,300 - $219,800. 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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