
Backend Software Engineer
Distyl
Job description
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As a Software Engineer Back End you will help design, build, and optimize Distillery—our AI-native platform that powers real-world enterprise AI systems for diverse F500 workflows
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Your role will involve developing scalable AI infrastructure, ensuring system reliability, and collaborating with engineers and business leaders to solve some of the most complex AI deployment challenges
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Build & Scale AI-Native Infrastructure: Develop and refine a platform where AI builds, optimizes, and operates AI-powered workflows. Define how AI automation integrates into traditional enterprise infrastructure
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Develop Cloud-Native Microservices & Scalable AI Systems: Design and build secure, high-performance backend services deployed across AWS/GCP/Azure or on-prem Kubernetes environments. Build using Python, FastAPI, SQLAlchemy, Alembic, and modern DevOps tools to develop scalable, reliable AI infrastructure
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Optimize System Performance & Reliability: Ensure high-availability, security, and observability of AI-native workflows. Implement best practices for ML/AI Ops, distributed computing, and scalable service orchestration
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Collaborate with Cross-Functional Teams: Partner with Forward-Deployed Engineers (FDEs), AI Researchers, and business SMEs to translate real-world operational needs into platform capabilities. Advocate for strong software engineering and DevOps practices, driving high coding standards and scalable architectures
Benefits
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Equity options and healthcare
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Collaborative and supportive work environment
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Strong focus on personal and professional growth- Strong interest in AI-native development, leveraging tools like ChatGPT, Claude, Perplexity, and Cursor in engineering workflows
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We are hiring multiple roles across different levels of seniority (3-10+ years of software engineering experience)
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Experience with security, distributed systems, storage, ML/AI Ops, and large-scale observability is a plus
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Proficiency in Backend & Systems Engineering. Expertise in Python, Java, Golang, or C++ for building scalable, high-performance systems
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Hands-on experience with Kubernetes, CI/CD, cloud platforms (AWS, GCP, or Azure), and infrastructure as code