Member of Technical Staff, Infra
Summary
Build and scale backend systems for Abaka AI’s AI-native platform, including APIs, data models, and cloud infrastructure to support high-performance AI systems.
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Own the architecture of Abaka Expert Platform's shared backend systems—core services, data models, APIs, and cross-product infrastructure.
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Define and drive the long-term technical strategy for backend architecture across the organization.
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Design, build, and ship backend services and APIs that power AI-native product features at scale.
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Design systems for scale, reliability, and evolvability, and lead the highest-stakes technical decisions and design reviews.
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Establish backend engineering standards, patterns, and best practices adopted across all product teams.
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Partner closely with Product and AI/ML teams to translate product and model requirements into production-grade systems.
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Use modern AI development tools.
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Improve performance, reliability, and observability of existing backend infrastructure
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Debug and resolve production issues
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3+ years of professional backend software engineering experience
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Strong expertise in backend: API design, data modeling, distributed systems, databases, and API design at scale.
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A track record of owning architecture across multiple teams or an entire organization—and of decisions that aged well.
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Capable in a modern frontend framework (React/TypeScript) and able to work the full path from UI to backend when needed
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Product-minded: you push back on unnecessary complexity and think about the customer outcome the system enables.
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Excellent communication skills—able to make complex tradeoffs legible to both engineers and leadership.
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Experience building or integrating AI/LLM-powered features and agent designs
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Fluent with modern AI development tools (e.g., Cursor, Claude Code, GitHub Copilot, or similar) as part of your daily workflow.
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Comfortable with ambiguity and evolving priorities
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High ownership, pragmatism, and a bias toward shipping.
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Startup or founder experience
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Experience building consumer-facing products at scale.
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ML and Deep Learning knowledge and experience