• Develop and maintain backend services using Python and Django. • Work extensively with Django ORM and complex database queries. • Build and maintain data pipelines and feed ingestion systems (XML, APIs). • Implement background processing using Celery and Redis. • Integrate with third-party systems, including ATS platforms such as Greenhouse, Lever, or iCIMS. • Optimize PostgreSQL databases and backend performance. • Support job distribution systems and data workflows. • Troubleshoot and resolve backend issues across services. • Collaborate with cross-functional teams to deliver scalable solutions. • Take ownership of backend features end-to-end.

• Design, develop, and maintain scalable and secure backend services using C# and .NET/.NET Core. • Build and document RESTful APIs for internal and external consumption. • Implement data access layers using Entity Framework Core. • Write clean, maintainable, and testable code following best practices and design patterns (Decorators, Commands). • Participate in code reviews, provide constructive feedback, and ensure adherence to coding standards. • Troubleshoot, debug, and resolve application issues in production and development environments. • Integrate with third-party APIs and services, ensuring reliability and performance. • Contribute to the architecture and design of microservices and distributed systems. • Maintain CI/CD pipelines and support automated deployment processes. • Keep up-to-date with emerging backend technologies and recommend improvements.

• Contribute to building an efficient and scalable backend data model. • Build and maintain critical backend integrations (e.g., VCS providers). • Build and maintain the backend web server. • Design, build, and maintain internal APIs for our web application. • Build and maintain backend APIs for our Model Context Protocol (MCP) products. • Bring strong architectural instincts to the team. • Embrace AI-assisted development. • Communicate effectively with team members and across key team interfaces.

• Development of RPA automations (low, medium, and high complexity) • Technical leadership in the development and evolution of bots • Design and definition of scalable automation architecture • Integration of systems via APIs (REST/Web Services) • Use of generative AI to optimize code and productivity • Development of ETL processes and data engineering • Testing, validation, and maintenance/support of bots in production • Monitoring and continuous improvement of automations • Technical support to the team and dissemination of best practices • Interaction with business areas and stakeholders