
51 - 200 employees
💸 Finance
💳 Fintech
☁️ SaaS
Finance • Fintech • SaaS
Ledgy is a modern equity management platform designed to streamline equity workflows for private and public companies. It provides comprehensive solutions such as cap table management, equity plan automation, employee engagement, financial reporting, and compliance. Ledgy's platform gives users the ability to automate manual processes, manage data efficiently, and stay audit-ready across jurisdictions. It is highly focused on providing real-time insights and access, ensuring that employee and stakeholder communications are clear and effective. Ledgy is committed to offering robust security and compliance measures, making it a reliable choice for international teams looking to manage equity seamlessly and accurately.
🔥 0 minutes ago
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51 - 200 employees
💸 Finance
💳 Fintech
☁️ SaaS
Finance • Fintech • SaaS
Ledgy is a modern equity management platform designed to streamline equity workflows for private and public companies. It provides comprehensive solutions such as cap table management, equity plan automation, employee engagement, financial reporting, and compliance. Ledgy's platform gives users the ability to automate manual processes, manage data efficiently, and stay audit-ready across jurisdictions. It is highly focused on providing real-time insights and access, ensuring that employee and stakeholder communications are clear and effective. Ledgy is committed to offering robust security and compliance measures, making it a reliable choice for international teams looking to manage equity seamlessly and accurately.
• Lead a team of 4–6 engineers building Ledgy’s agent and developer platform • Set technical direction and create an environment for engineers to do their best work • Own and improve CI/CD build and deployment pipelines for speed, reliability, and human/AI-agent workflows • Manage GCP infrastructure, Terraform configuration, monitoring, alerting, and SLOs • Partner with the CISO to define and execute Ledgy’s security strategy • Build AI infrastructure and agent-platform capabilities, including MCP interfaces, agent identity and access models, audit logging, dry-run environments, and sandboxes • Establish relationships with direct reports and support their career growth • Drive measurable improvements in pipeline reliability, deployment velocity, developer experience, and infrastructure reliability • Shape platform strategy with the Head of Engineering and CTO • Lead career development conversations and performance reviews • Own engineering initiatives influencing how the organisation ships software
• Strong vision for modern platform engineering with AI agents writing, testing, and deploying code alongside humans • Deep experience in CI/CD, DevOps, and infrastructure • Experience with observability, deployment automation, developer experience, and infrastructure-as-code • Security-minded approach to platform engineering, including AI-agent access to production systems and sensitive financial data • People development and engineering management capabilities • Hands-on experience with Terraform, pipeline debugging, and AI tools • 3+ years of Engineering Management experience • 6+ years of Software Engineering experience • Meaningful experience in platform, infrastructure, or DevOps roles • Experience with TypeScript, React, Tailwind CSS, tRPC, Node.js, MongoDB, Temporal, GCP, Terraform Cloud, Kubernetes, Docker, and GitHub Actions • Completion of live coding and system design interview stages
• Flexible working hours • 25 days of vacation • Up to 40 days of remote work from outside your home country • Generous yearly learning & development budget • Competitive salary • Benefits • Equity
Apply Now🕒 July 27
Backend Software Engineer focusing on AI/ML backend services in Python. Responsible for designing and implementing scalable backend services and managing AI-driven data pipelines.
AWS
Azure
Cloud
Django
Docker
Flask
Google Cloud Platform
Grafana
GRPC
Numpy
Pandas
Prometheus
Python
Scikit-Learn
SQL
🕒 July 8
Senior AI ML Engineer at 3Pillar, designing cloud-native platforms for AI and data workloads. Building scalable data pipelines and collaborating with cross-functional teams for digital transformation.
AWS
Cloud
Docker
Python
TypeScript