Source description
About the role
Architect and implement AI-powered features end-to-end, from model integration and prompt engineering to deployment, monitoring, and iteration
Integrate LLM APIs, ML models, and intelligent automation pipelines into scalable, production-grade backend systems
Fine-tune and optimize models for performance, reliability, and cost efficiency in live environments
Design and build robust APIs, event-driven services, and third-party integrations that support AI-enabled workflows
Collaborate with Product to translate business requirements into technical AI solutions, defining scope, complexity, and dependencies
Build and maintain data pipelines and MLOps workflows to support model deployment and lifecycle management
Contribute to system architecture decisions, integration patterns, and reusable AI frameworks across the platform
Partner with data scientists and engineers to ensure smooth, scalable model deployments
Produce clear technical documentation, architecture diagrams, data flows, API specs, and AI integration patterns
Lead code reviews, enforce best practices in code quality and testing, and mentor engineers across teams
Troubleshoot complex production issues across distributed and AI-integrated systems
Stay ahead of industry trends in AI/ML tooling, frameworks, and practices
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