Top Tech Jobs & Startup Jobs

Lead architecture and development of production-grade agentic AI and multi-agent systems for reliability engineering. Design autonomous agents, manage AI infrastructure and deployment, ensure observability/security/guardrails, automate remediation, evaluate vendors and models, and produce secure, high-quality production code to improve system reliability and engineering productivity.

Lead technology risk and controls for AI and broader tech environments: identify, quantify, and mitigate compliance and operational risks; provide SME guidance to technologists; use enterprise AI to synthesize evidence and reporting; govern controls, monitor effectiveness, recommend enhancements, and influence executive decision-making.

Lead technology risk identification, assessment, and control evaluation within CORE. Support Technology Control Managers, maintain data quality and reporting, implement controls with cross-functional teams, and validate AI-assisted risk evidence and remediation recommendations to strengthen governance, compliance, and operational risk posture.

Lead independent oversight of the firm's capital risk across North America: set capital risk assessment, limits, governance; perform deep-dive analyses; support stress testing and capital planning; present insights to senior management; oversee credit risk transfer review; engage regulators and internal partners; manage and develop a high-performing team to ensure capital resiliency and regulatory compliance.

Lead an agile engineering team to design, build, review, and maintain secure, high-quality production software. Provide technical direction, drive product and architecture decisions, champion firmwide SDLC practices and AI-assisted engineering, and ensure operational stability and reusable automation across cloud-native applications.

Lead technology risk identification, assessment, and control evaluation within CORE. Support Technology Control Managers, ensure data quality and program hygiene, implement controls with stakeholders, and validate AI-assisted risk evidence and remediation recommendations to maintain compliance with firm standards and regulatory requirements.

Lead design and delivery of reliable, scalable AI/ML platform services. Build production-grade code, reusable APIs/SDKs, observability and resilience tooling, define reliability standards, support on-call incident resolution, and mentor engineers to enable secure, compliant generative AI use cases.

Lead design and delivery of metadata, meta-modelling, and distributed systems. Build secure, high-quality production code, drive adoption of AI-assisted engineering, improve SDLC automation and cloud-native delivery, set validation and governance standards, mentor engineers, and influence product and technical decisions.

Lead implementation and enforcement of data governance and risk management policies. Manage data quality remediation, metadata, lineage, stakeholder coordination, BCBS 239 compliance, metrics, training, and enablement across business and technology partners.

Lead enterprise IT operations architecture: define strategy and governance, drive adoption of cloud-native, SRE, observability and AI-assisted solutions, create reusable frameworks, improve cost-performance and traceability, and evaluate emerging technologies for portfolio-wide fit.