Job DescriptionThe Lead Engineer will provide senior engineering leadership across two strategic teams: the Risk Data Team and the Risk AI Engineering Team. This role is accountable for setting technical direction, aligning engineering execution to business outcomes, and ensuring both teams deliver secure, scalable, reliable and measurable risk products.
The Risk Data Team creates the trusted data foundation for risk management by transforming fragmented risk and control data into reliable, accessible and actionable information. The team builds governed data products, integrates internal and external data sources, automates validation and reconciliation, develops dashboards and reporting, defines common metrics and quality standards, and reduces reliance on manual reporting.
The Risk AI Engineering Team designs and delivers secure, explainable and responsible AI capabilities within risk products. The team develops reusable AI capabilities, identifies high-value use cases, builds AI-assisted workflows, implements natural language, classification, recommendation and predictive features, and ensures appropriate human review, model evaluation, monitoring and continuous improvement.
Each team will be led day-to-day by a Managing Engineer. The Managing Engineers will report to the Lead Engineer, who will provide leadership across the combined engineering capability, ensure alignment between data and AI strategies, and create the conditions for both teams to deliver trusted, production-ready outcomes across TORC.
The Lead Engineer is responsible for leading a multi-team engineering function that brings together risk data, analytics, automation and AI capabilities. This role combines senior technical leadership, people leadership, delivery accountability and stakeholder influence. The Lead Engineer will guide the Managing Engineers, shape architecture and engineering practices, ensure strong production ownership, and partner across TORC, product, risk, control, governance, security and platform teams.
The role is accountable for ensuring the Risk Data Team provides high-quality, governed and AI-ready data foundations, while the Risk AI Engineering Team builds responsible, explainable and integrated AI capabilities that improve decision making, simplify complex risk activities and help the organization identify and respond to risk earlier.
Success in this role will be measured by the quality, reliability and adoption of the data and AI products delivered; measurable improvement in risk insight and control effectiveness; reductions in manual effort; strong engineering health; and the ability of both teams to deliver safe, scalable and trusted capabilities in production.
Key Responsibilities- Lead the combined Risk Data and Risk AI Engineering organization, providing strategic direction, accountability, and oversight across both teams.
- Manage and develop Managing Engineers while building leadership capability and strengthening engineering talent across the organization.
- Translate TORC strategy into engineering roadmaps, delivery plans, measurable goals, and technical priorities.
- Ensure delivery of trusted, governed, analytics-ready risk data products, dashboards, reporting, automation capabilities, and AI solutions embedded within risk workflows.
- Align data and AI strategies to ensure AI capabilities are built on reliable, high-quality, governed risk and control data.
- Establish technical direction across data engineering, analytics, AI engineering, automation, model evaluation, monitoring, and responsible AI practices.
- Drive engineering excellence through modern development practices, CI/CD, automated testing, observability, data quality controls, production support, and operational resilience.
- Define and enforce standards for data quality, governance, security, privacy, compliance, access controls, lineage, explainability, validation, and model performance monitoring.
- Partner with product, risk, control, governance, security, platform, and technology teams to align priorities, manage dependencies, influence adoption, and deliver measurable business outcomes.
Required Qualifications- Significant engineering leadership experience, including leading managers, senior engineers, and multiple delivery teams.
- Strong background in software engineering, data engineering, analytics engineering, AI engineering, or a related technical discipline.
- Proven experience building, operating, and supporting scalable, production-grade technology products and platforms.
- Demonstrated success setting technical direction and translating business strategy into actionable roadmaps, delivery priorities, and measurable outcomes.
- Strong understanding of modern engineering practices, including CI/CD, automated testing, code quality, observability, production support, security, and resilience.
- Experience with data platforms, data pipelines, analytics products, reporting automation, governed data products, and AI-enabled solutions.
- Knowledge of AI, machine learning, large language models, responsible AI, explainability, model evaluation, and AI-assisted workflow design.
- Strong stakeholder management skills with the ability to influence technical and non-technical audiences across product, engineering, risk, governance, security, and leadership teams.
- Proven ability to develop leaders, build high-performing teams, drive continuous improvement, and make sound architectural trade-offs across reliability, scalability, security, quality, and speed.
Preferred Qualifications- Experience working in risk, control, compliance, audit, cybersecurity, technology operations, or other regulated environments.
- Experience delivering data and analytics solutions using Microsoft Fabric, Power BI, lakehouse architectures, Python, SQL, cloud data platforms, or similar technologies.
- Experience integrating data from internal platforms, vendor solutions, operational systems, and external sources.
- Experience delivering AI solutions such as natural language capabilities, classification, recommendations, predictive models, or AI-assisted workflows.
- Familiarity with responsible AI practices, including governance, bias assessment, reliability testing, explainability, human oversight, and monitoring.
- Demonstrated success reducing manual processes, reporting, and spreadsheet dependency through automation and reusable data products.
- Experience leading complex cross-functional engineering initiatives spanning multiple teams, products, platforms, and stakeholder groups.
- Proven ability to establish enterprise-wide engineering standards, governance frameworks, and reusable technical patterns.
Education & Experience- 10+ years of relevant experience preferred.
- Supervisory/people leadership experience required.
#LI-SM1
SkillsAccess Management, Access Management, Artificial Intelligence (AI), Artificial Intelligence Techniques, Authentication, Authentication Protocols, Automated Deployments, AWS Secrets Manager, Certificate Services, Computer Science, Design, Engineering Leadership, Enterprise SSO, GitHub, GitHub Actions, Information Technology Management, Infrastructure as a Service (IaaS), Infrastructure As Code (IaC), Infrastructure Engineering, IT Security Operations, Just-in-Time (JIT) Manufacturing, Just in Time (JIT) Production, Kerberos, LDAP Authentication, Microsoft PowerShell {+ 21 more}
CompensationCompensation offered for this role is 151,700.00 - 221,675.00 annually and is based on experience and qualifications.
Allstate provides a comprehensive technology setup, including a laptop, monitors, headset, keyboard, and mouse. Employees eligible to work from home also receive a monthly connectivity reimbursement to help offset internet costs.
When working from home, you must have a dedicated, private workspace free from distractions, along with appropriate desk and seating. Reliable internet is required, with minimum speeds of 50 MB download and 5 MB upload.
To help create a more personal and engaging experience, we ask that you join with your camera on if your interview is virtual. Please also have a Valid Photo Identification available at the start of your interview. If you require any accommodations or have questions ahead of your interview please reach out to your recruiter.
Note: Internal candidates are only asked to join on video; a Valid Photo Identification is not needed for the interview.
