Managing Engineer - Risk Data & AI (Remote, US)
About The Position
Risk Data & AI designs, builds, and operates governed data products, analytics solutions, and AI-enabled capabilities that support risk and compliance decision-making. The team applies modern data, software, and AI engineering practices to deliver scalable data pipelines, trusted analytical products, intelligent automation, and responsible AI solutions. These capabilities help TORC identify emerging risks, generate actionable insights, and make timely, evidence-based decisions. The Managing Engineer is a hands-on engineering leader responsible for leading teams that build, deliver, and operate data and AI products in production. The role combines technical leadership, people leadership, and delivery ownership to ensure solutions are scalable, reliable, secure, and responsibly implemented, with measurable business and engineering impact.
Requirements
- 5+ years of data, analytics, or AI engineering experience, including hands-on development in Python and/or Java and delivery of production-grade AI solutions.
- 2+ years leading engineers with technical guidance across architecture, design, code reviews, engineering standards, and delivery coaching.
- Experience with APIs, backend services, data pipelines, and analytical/reporting systems.
- Experience delivering AI-enabled applications, Generative AI solutions, or intelligent automation capabilities.
- Knowledge of modern engineering practices, including DevSecOps, CI/CD pipelines, testing, monitoring, and observability.
- Experience with Generative AI frameworks, large language models, prompt engineering, and AI orchestration frameworks.
- Experience building Retrieval-Augmented Generation (RAG) solutions using enterprise data and vector databases.
- Experience working in agile environments delivering data, analytics, or AI solutions.
Nice To Haves
- Experience in risk, compliance, security, governance, or technology operations domains.
- Experience with MLOps, AI model deployment, evaluation, monitoring, and operationalization.
- Exposure to agentic AI, multi-agent systems, AI copilots, or intelligent workflow automation.
- Ability to influence adoption of standards, reusable patterns, and scalable engineering solutions across teams.
- Experience mentoring senior engineers and developing technical leaders.
- Strong stakeholder management and ability to navigate cross-team dependencies.
- Commitment to building scalable, reliable, responsible, and low-friction data and AI solutions that improve organizational outcomes.
Responsibilities
- Lead and manage a team delivering data products, AI-enabled applications, intelligent automation capabilities, and enterprise data platforms.
- Set technical direction across data engineering, AI engineering, application development, deployment, and operational support.
- Contribute hands-on to architecture, design decisions, AI solution patterns, and critical-path development.
- Own production outcomes, including system reliability, data quality, application performance, model effectiveness, and operational health.
- Partner with Digital Product Managers, data teams, AI teams, and engineering organizations to align roadmaps, priorities, and delivery outcomes.
- Drive modern engineering practices, including TDD, CI/CD, observability, MLOps, automated testing, and responsible AI implementation.
- Translate business, risk, and compliance requirements into scalable data, analytics, and AI-powered solutions and reusable engineering patterns.
- Influence adoption of enterprise data standards, AI engineering best practices, and platform-integrated capabilities.
- Lead agile execution with a focus on measurable business outcomes, engineering excellence, and continuous delivery.
Benefits
- Comprehensive technology setup, including a laptop, monitors, headset, keyboard, and mouse.
- Monthly connectivity reimbursement for employees eligible to work from home.
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What This Job Offers
Job Type
Full-time
Career Level
Manager
Education Level
No Education Listed
