About the Role
The role involves leading the development of core AI systems within a fintech foundation, ensuring high performance, security, and scalability while collaborating with data scientists and product teams.
Responsibilities
- Design and implement scalable backend services for financial applications
- Integrate machine learning models into production environments
- Optimize system performance and data processing pipelines
- Ensure compliance with financial data security standards
- Collaborate with data science teams on model deployment
- Write clean, maintainable, and well-documented code
- Lead technical design discussions and architecture planning
- Troubleshoot and resolve production issues promptly
- Mentor junior engineers and conduct code reviews
- Work with infrastructure teams on cloud deployment strategies
- Monitor system health and implement alerting mechanisms
- Improve CI/CD workflows for faster, safer releases
- Evaluate new technologies for potential integration
- Participate in sprint planning and agile ceremonies
- Ensure software meets audit and regulatory requirements
- Develop APIs for internal and external partners
- Conduct performance benchmarking and load testing
- Maintain documentation for systems and processes
- Support integration with third-party financial platforms
- Drive improvements in system observability and logging
- Collaborate on fraud detection and risk modeling features
- Implement data encryption and access control protocols
- Refactor legacy components for better maintainability
- Contribute to disaster recovery and backup strategies
- Promote best practices in software engineering across teams
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid remote with office presence in major tech hubs
Team
Cross-functional team building AI-driven financial infrastructure
Technology Stack
- Primary languages: Python, Java
- Cloud infrastructure: AWS, GCP
- Container orchestration: Kubernetes
- Databases: PostgreSQL, MongoDB
- ML frameworks: TensorFlow, PyTorch
Team Culture
- Emphasis on technical excellence
- Open feedback and continuous learning
- Flat organizational structure
- Regular knowledge-sharing sessions
- Focus on work-life balance
Available for qualified candidates
