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Senior Full-Stack Engineer - Team Optimize(m/w/x)
Building Python-based backend components for automated decisioning software at a fraud detection and credit expansion platform. 7+ years backend engineering experience with large-scale data performance required. Top-of-market equity and cash compensation.
Requirements
- 7+ years of backend engineering experience
- Experience building customer-facing platforms
- Comfort with large-scale data performance
- Industry experience with Python or Java
- Experience with AWS and serverless architectures
- Fluent written and spoken English
- Interest in AI-driven automation and tools
- Experience with Iceberg, Athena, or Spark
- Experience with React and TypeScript
- Experience building experimentation or evaluation systems
- Exposure to risk or financial domains
Tasks
- Build and own Python-based backend components
- Design complex subsystems for large-scale decision data
- Maintain well-structured APIs using FastAPI
- Review pull requests to ensure high code quality
- Contribute to architectural decisions and CI/CD improvements
- Collaborate with Product and Solutions teams
- Translate business problems into scalable technical solutions
- Participate in planning sessions and technical deep dives
- Manage systems processing millions of daily decisions
- Execute large-scale experiments over billions of historical records
Work Experience
- 7 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Java
- AWS
- Apache Iceberg
- Athena
- Spark
- React
- TypeScript
Benefits
Competitive Pay
- Top-of-market equity
- Top-of-market cash compensation
Informal Culture
- Supportive and collaborative colleagues
- Flat hierarchy
Startup Environment
- Direct communication with founders
- Access to investor network
Mentorship & Coaching
- Experienced mentors
Additional Allowances
- Self-development budget
Modern Equipment
- New Apple MacBook Pro
- Home office set-up
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Senior Full-Stack Engineer - Team Optimize(m/w/x)
Building Python-based backend components for automated decisioning software at a fraud detection and credit expansion platform. 7+ years backend engineering experience with large-scale data performance required. Top-of-market equity and cash compensation.
Requirements
- 7+ years of backend engineering experience
- Experience building customer-facing platforms
- Comfort with large-scale data performance
- Industry experience with Python or Java
- Experience with AWS and serverless architectures
- Fluent written and spoken English
- Interest in AI-driven automation and tools
- Experience with Iceberg, Athena, or Spark
- Experience with React and TypeScript
- Experience building experimentation or evaluation systems
- Exposure to risk or financial domains
Tasks
- Build and own Python-based backend components
- Design complex subsystems for large-scale decision data
- Maintain well-structured APIs using FastAPI
- Review pull requests to ensure high code quality
- Contribute to architectural decisions and CI/CD improvements
- Collaborate with Product and Solutions teams
- Translate business problems into scalable technical solutions
- Participate in planning sessions and technical deep dives
- Manage systems processing millions of daily decisions
- Execute large-scale experiments over billions of historical records
Work Experience
- 7 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Java
- AWS
- Apache Iceberg
- Athena
- Spark
- React
- TypeScript
Benefits
Competitive Pay
- Top-of-market equity
- Top-of-market cash compensation
Informal Culture
- Supportive and collaborative colleagues
- Flat hierarchy
Startup Environment
- Direct communication with founders
- Access to investor network
Mentorship & Coaching
- Experienced mentors
Additional Allowances
- Self-development budget
Modern Equipment
- New Apple MacBook Pro
- Home office set-up
About the Company
Taktile
Industry
FinancialServices
Description
The company is building a leading software platform for automated decisioning, helping to catch fraud and expand access to credit.
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