The 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.
Compensation
170,000 - 221,750 annually
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.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality.
Responsibilities
Design and build advanced AI applications and systems
Manage end-to-end application pipelines
Integrate generative AI models into projects
Develop neural network architectures
Implement intelligent systems such as chatbots and image processing tools
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Design and build advanced AI applications and systems
Manage end-to-end application pipelines
Integrate generative AI models into projects
Develop neural network architectures
Implement intelligent systems such as chatbots and image processing tools
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Design and build advanced AI applications and systems
Manage end-to-end application pipelines
Integrate generative AI models into projects
Develop neural network architectures
Implement intelligent systems such as chatbots and image processing tools
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with stakeholders to understand project requirements and translate them into technical solutions.
Continuously monitor and optimize AI models and systems to maintain high performance and reliability.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Design and build advanced AI applications and systems
Manage end-to-end application pipelines
Integrate generative AI models into projects
Develop neural network architectures
Implement intelligent systems such as chatbots and image processing tools
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with stakeholders to understand project requirements and translate them into technical solutions.
Continuously monitor and optimize AI models and systems to maintain high performance and reliability.
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