Managing Engineer - Risk Data & AI (Remote, US)

Overview

Lead and manage a team that builds, delivers and operates governed data products, analytics solutions and AI-enabled capabilities supporting risk and compliance decision-making, acting as a hands-on engineering leader.

What you'll do

• 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.
• Act as a hands-on leader contributing 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 strong focus on measurable business outcomes, engineering excellence, and continuous delivery.

What you'll need

• 5+ years of data, analytics, or AI engineering experience with 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 have

• 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.

Details

• Location: USA - IL (Remote)
• Compensation: 120,000.00 - 193,725.00 annually, based on experience and qualifications.
• Subject to a background investigation.
• Generally does not sponsor individuals for employment-based visas for this position.