Senior Product Engineer

Design and build backend services for financial workflows.

Collaborate with product and engineering teams on scalable solutions.

Design and develop agentic systems for automating workflows.

Translate customer needs into agent behaviors.

Design agentic systems for audit workflows.

Translate customer problems into agent behaviors.

Develop frontend applications using TypeScript.

Contribute to backend services in Python.

Deliver high-quality features with minimal guidance.

Participate in design reviews for team-wide technical solutions.

Develop scalable and reliable software solutions.

Maintain high code quality through reviews.

Lead backend development projects.

Collaborate across multiple engineering teams.

Act as a technical expert for sales.

Deliver educational demos to customers.

Protect the seller funnel from fraud and abuse.

Enhance seller onboarding and education.

Develop agent infrastructure for orchestration and tool execution.

Create an AI assistant that integrates with Slack and dashboards.

Design and implement data pipelines.

Build secure data warehousing solutions.

Build internal content and media systems for architecture and storytelling.

Create automation and repository infrastructure for design assets.

Design and build authentication services.

Lead migration to modern platform services.

Design and implement backend systems in Rust.

Collaborate across teams for improved performance.

Lead development of HR and Payroll projects.

Provide technical feedback and solutions.

Lead backend projects for HR/Payroll products.

Contribute to product development and feedback.

Own model evaluation processes end-to-end.

Build and maintain benchmarking pipelines.

Architect scalable web systems.

Implement distributed caching strategies.

Design and maintain scalable datasets.

Improve data pipelines with Marketing Analytics and BI.

Build foundational platform infrastructure.

Improve developer productivity with dev environments and CI/CD.

Design scalable data pipelines for CS.

Develop data models for reporting and ML.

Design and implement CIAM backends.

Develop secure authentication flows.

Deliver features in collaboration with Product Managers and Designers.

Support both frontend and backend development.

Lead a team of 25 engineers across product teams.

Define AI-first engineering standards and workflows.

Own and scale systems from conception to production.

Rapidly prototype and iterate based on real usage.

Develop and deploy full features.

Support and evolve core infrastructure.

Manage and optimize LMS and integrations.

Architect and monitor data pipelines.

Lead major team projects for HR/Payroll products.

Provide technical feedback for cross-team initiatives.

Manage backend application development.

Build scalable solutions for Business Intelligence.

Collaborate across functions on use cases.

Gain insights from executives, including Founders and CEO.

Define and drive EA strategy across core applications.

Lead the Architecture Review Board and enforce TOGAF standards.

Own AI platform architecture and APIs.

Lead build-vs-buy decisions for AI components.

Lead major projects in HR/Payroll products.

Participate in product work and provide technical feedback.

Design and develop cloud-native API-first platforms.

Lead the transition to cloud-native architecture.

Develop applications using Python and other languages.

Implement RAG architectures for enhanced functionality.

Support design and development of Generative AI solutions.

Implement core RAG pipelines for AI applications.

Optimize the data backend using Snowflake.

Create effective data models and pipelines.

Build and ship full-stack applications.

Design and implement AI agents.

Identify and build high-leverage opportunities.

Prototype and ship solutions with cross-functional teams.

Design scalable APIs using Go.

Enforce coding and testing best practices.

Define product strategy for Activation suite.

Collaborate with engineering teams on campaign management.

Develop backend features for data management.

Collaborate with cross-functional teams on reliable solutions.

Lead development of cross-system features.

Deliver scalable AI-native applications.

Identify AI enablement needs across the organization.

Collaborate to define metrics and tools for improvement.

Design and build data ecosystems.

Own end-to-end data pipelines.

Design and develop scalable data models for analytics.

Collaborate with cross-functional teams for insights.

Connect top developers with global opportunities.

Lead design and implementation of backend services.

Create a reusable media production system.

Establish governance and structure for asset management.

Lead a team of engineers.

Develop and maintain web applications.

Establish architectural vision and strategy.

Lead API integrations and pharmacy fulfillment.