Build and deploy AI-enabled solutions across investment, finance, compliance and operations teams, combining full-stack engineering, data pipelines, system integrations and AI experimentation.
Compensation
Compensation range: CAD$90,000 to CAD$130,000
Responsibilities
Partner with business units across investment, finance, compliance and operations to understand operational problems, scope technical solutions, and rapidly prototype and iterate based on real-world feedback.
Design and build data pipelines that move, transform, and prepare data from internal systems for use in AI and analytics workflows.
Own end-to-end integrations between internal platforms and third-party APIs, including authentication, error handling, and ongoing maintenance.
Contribute to foundational infrastructure decisions – data storage, service architecture, deployment patterns – as the firm's data and AI platform matures.
Build and deploy production-ready AI applications, including RAG pipelines, agentic workflows, and LLM integrations, with a pragmatic eye toward what actually works at scale.
Requirements
Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience.
Nice to have: experience in financial services or alternative asset management
Nice to have: familiarity with structured financial data
A hands-on role for a senior engineer to reshape how the whole company works using AI, starting in development and owning end-to-end business capabilities like reconciliation and IT operations.
Responsibilities
Own the way engineering works with AI, including the agent harness, shared repository, and compliance-gated pipeline
Define the method for agent usage, work specification, output review, and testing
Map and improve business capabilities such as reconciliation, funds management, and IT operations
Use agents to create platform specifications and automate evidence for control frameworks
Build guardrails for engineers to use AI-powered tooling safely
End-to-end responsibility for the technical design, quality, and scalability of complex AI solutions in business-critical contexts, acting as a bridge between business requirements and technical implementation.
Responsibilities
Overall technical responsibility for the architecture, technical consistency, and delivery quality of AI and Agentic AI solutions.
Translating complex business requirements into viable, scalable, and secure AI architectures.
Definition and enforcement of architecture, design, and quality standards.
Design and implementation of agent-based systems (orchestration, tool use, decision logic, persistence strategies).
Evaluation and selection of appropriate agentic patterns, frameworks, and platform services in the Azure ecosystem.
Own the strategy for capturing, structuring, and compounding sourcing data into a proprietary asset to make the platform smarter and defensible.
Compensation
The anticipated annual base salary range for this position is $150,000 - $250,000. Actual compensation may vary based on factors such as experience, skills, and location.
Responsibilities
Own the data product strategy and roadmap, defining how Globality captures customer data
Identify which data creates durable competitive advantage
Design the instrumentation strategy that captures high-value signals
Define canonical data models, taxonomies, and entity resolution
Build feedback loops that turn sourcing outcomes into training data and benchmarks
Build and operate AI infrastructure on Azure, develop and deploy AI models and agents, ensure compliance with healthcare data regulations, and mentor engineering teams.
Responsibilities
Provision AI infrastructure on Azure as code
Stand up open-weight and frontier models
Develop technical policies and controls
Run shared model access across providers
Build sandboxed environments for coding agents
Requirements
Bachelor's Degree in Computer Science, Engineering or a related field
We are looking for a hands-on Senior or Staff Security Engineer to lead and own security across the company, focusing on hardened cloud infrastructure, vulnerability management, and AI-specific risks.
Responsibilities
Set security priorities and drive fixes through to verified completion
Find application vulnerabilities through code review, penetration testing and agent-specific red-team exercises
Work with ITOps, platform and product engineers to harden infrastructure and build security into delivery pipelines
Build detection for user and agent activity, and lead incident response
Requirements
Nice to have: Securing sandboxed or multi-tenant execution environments
Lead and grow the Kalepa for Underwriting engineering team, define architectural roadmap, drive operational excellence, and cultivate a high-performance culture.
Locations (2)
United States
Canada
Compensation
We differentiate our North America salary ranges using two geographical zones:
Zone 1 (New York and San Francisco) - $260,000 to $350,000*
Zone 2 (all other locations in the US and Canada) - $230,000 to $350,000*
Responsibilities
Lead and grow the engineering team
Define architectural roadmap and technical strategy
Establish engineering standards and cross-functional cadences
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