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The SDET at Aftershoot will develop and drive automation strategies, design test frameworks, collaborate with teams, and enhance CI/CD processes to assure product quality and stability.

As a Senior Software Engineer, you will develop and maintain Electron desktop applications, optimize performance, and ensure smooth cross-platform collaboration, from planning to monitoring.

Build and optimize a local high-performance Rust backend that communicates with an Electron frontend. Implement IPC and APIs, manage local persistence/storage, and optimize CPU/memory/disk I/O for AI-driven photo workflows.

Design, implement, and maintain scalable cloud infrastructure and microservices (preferably on GCP). Develop and operate Docker-based services, implement IaC, and build observability with Grafana/Prometheus. Contribute Go code and support event-driven/data pipeline integrations.

Design, build, and maintain scalable automated test frameworks (UI and API). Integrate tests into CI/CD, define testing strategy and KPIs, collaborate with product and engineering to ensure reliable releases, identify risks, and lead issue resolution to improve product quality and performance.

Lead end-to-end development of computer vision and generative AI systems: research, design, train, optimize, deploy, and monitor production ML models, collaborating with product and engineering teams.

Lead product strategy, roadmap, and execution for Aftershoot's AI-powered creative products. Collaborate with design, engineering, and marketing to define requirements, launch features, and iterate using qualitative and quantitative data to drive adoption, engagement, and retention.

Lead end-to-end design, development, deployment, and monitoring of computer vision and generative AI systems. Optimize training/inference pipelines, collaborate cross-functionally, and drive scalable production solutions for photography-related vision use cases.

Lead Aftershoot's AI/ML function: define roadmap, drive end-to-end computer vision model development, optimize models for edge/mobile, build and mentor an ML research and engineering team, and translate AI advancements into product features.

Lead product design from concept to execution: own key areas, run and synthesize user research, craft user-centered solutions, evolve the design system, iterate using data and testing, collaborate cross-functionally, mentor junior designers, and promote design-led decision making.