Software Engineering Manager

Are you ready to lead analytics engineers in turning AI from experimentation into trusted, production‑grade capabilities—without compromising security or governance?

About the Business:

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti‑Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below,

About the Team:

This position provides leadership, management, direction, and vision to data engineering and/or employees including offshore contractors/consultants and interns needed to oversee statistical and analytical data analysis. The position works closely with technology peers, product and project leaders/managers, as well as directing the successful completion and delivery of respective data components and any other related deliverables. The position is additionally expected to report progress to senior management. Additional responsibilities may include oversight of the department budget, identifying and supporting talent, and defining resource requirements and allocations.

About the Role:

This role leads to the Analytics Engineering function with a focus on embedding AI into delivery while ensuring strong InfoSec and data governance standards . It sits at the intersection of engineering, AI, and risk—driving practical adoption of AI in analytics workflows without compromising compliance or control.

Responsibilities:

Team Leadership & Delivery: Lead and support analytics engineers, ensuring clear priorities and consistent delivery. Remove blockers, drive accountability, and maintain pace across initiatives.

AI Adoption in Analytics: Identify and prioritize high‑impact AI use cases (e.g. LLM‑driven parsing, enrichment, copilots). Embed AI into pipelines and workflows—not as experiments, but as part of production delivery. Guide teams on practical implementation and evaluation of AI outputs.

InfoSec & Governance: Ensure all AI and data usage aligns with internal InfoSec, privacy, and regulatory requirements. Define and enforce standards for safe AI usage (e.g. PII handling, approved models, access control). Work closely with InfoSec and architecture teams on risk management and approvals.

Data Quality & Control: Establish validation frameworks for AI outputs (e.g. Benchmarking, HITL, drift monitoring). Maintain strong data governance, lineage, and quality across analytics assets.

Stakeholder Engagement: Partner with product, business, and platform teams to align priorities and use cases. Translating business needs into scalable analytics and AI solutions.

Requirements:

• Bachelor’s Degree (Engineering/Computer Science preferred but not required); or equivalent experience required. Advanced degree preferred.
• Proven experience in Data and Scoring Engineering, data management and data strategy experience with technical knowledge along with management experience.
• Strong background in analytics engineering / data engineering (SQL, data modelling, modern data platforms).
• Experience applying AI/LLMs in production use cases , not just experimentation.
• Solid understanding of data governance, InfoSec, and regulatory considerations (PII, model risk, access control).
• Proven experience leading teams and driving delivery in a fast‑paced environment.
• Ability to balance innovation with control —moving quickly without introducing risk.
• Strong communication skills across both technical and business stakeholders.

Nice to Have:

• Experience with platforms such as Databricks, Synapse, Power BI.
• Familiarity with agent‑based workflows, prompt engineering, and evaluation frameworks.
• Exposure to regulated environments or sensitive data domains.

Success Measures:

• AI capabilities embedded into core analytics workflows.
• Clear governance model for AI usage adopted across the team.
• Improved delivery pace and reduced rework through better coordination.
• High trust in data and AI output from business stakeholders.

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:

• Medical Inpatient and Outpatient Insurance: Coverage for your healthcare needs.
• Life Assurance Policies: Providing financial security for your loved ones.
• Modern Family Benefits: Support for maternity, paternity, and adoption needs.
• Long Service Award: Recognition for your dedication and loyalty.
• Celebratory Allowance/Gifts: Marking special occasions to celebrate with you.
• Flexible Benefits Plan: Offering you wider choice of services and products.
• Employee Assistance Program: Access support for personal and work‑related challenges.
• Flexible Working Arrangements: Balance work and personal life effectively.
• Access to Learning and Development Resources: Empowering your professional growth.