Requirements

• The engineering challenge is building systems reliable enough to power these high-stakes decisions. You'll work across data pipelines processing billions of tokens, real-time simulation platforms, and B2B SaaS products that make complex AI feel intuitive
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• (Desirable) Experience with Python, TypeScript/JavaScript, PostgreSQL, or Google Cloud Platform
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• Strong software engineering fundamentals with experience in modern programming languages
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• (Desirable) Background in building scalable systems, APIs, and data-intensive applications
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• Proven track record of shipping production software and taking ownership of systems end-to-end
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• (Desirable) Familiarity with AI/ML systems, large language models, or high-throughput data processing
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• Experience working collaboratively in cross-functional teams with diverse technical backgrounds
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• (Desirable) Experience with GitHub Actions, CI/CD pipelines, monitoring, and observability
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• Strong problem-solving skills with the ability to debug and optimize systems across different domains
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• (Desirable) Interest in market research, behavioral science, or business applications of AI
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• Excellent communication skills and genuine interest in understanding client and business needs
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• Comfortable working in dynamic environments where business priorities drive technical decisions
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• Willingness to work with our tech stack: Python (server-side), TypeScript/JavaScript (client-side), PostgreSQL, GitHub, and Google Cloud Platform

What the job involves

• Build Production Systems: Develop and maintain our Python-based platform that powers synthetic population simulations, working with PostgreSQL databases and deploying on Google Cloud Platform
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• Deliver Client Impact: Create TypeScript/JavaScript B2B SaaS products that solve real business problems for major brands, working directly with product and commercial teams
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• Ensure System Reliability: Implement monitoring, testing, and GitHub Actions CI/CD pipelines to maintain high availability for systems that influence million-pound business decisions
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• Collaborate Across Disciplines: Partner closely with our data science team to translate research innovations into robust, scalable production systems
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• Drive Technical Excellence: Contribute to engineering standards and systematic approaches as we scale our platform and grow the team
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• Solve Diverse Challenges: Work across different technical domains - from optimizing data processing pipelines to building intuitive B2B SaaS experiences to ensuring system performance under high load