Senior Back End Engineer
Posted 20 days ago · 47 applicants
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The role in plain words
You will design, build, and maintain scalable backend services and microservices that integrate LLMs, computer vision models, and AI workflows into production. Day-to-day tasks include developing APIs for trade risk analysis, designing distributed services to process large volumes of customs data, and collaborating with AI and data engineers to operationalize machine learning models.
- 5+ years of experience building large-scale backend or distributed software systems
- Strong experience designing and building scalable distributed systems and microservice architectures
- Excellent Python development skills and hands-on experience using AI-assisted software development tools
- Hands-on experience integrating LLMs or AI services into production applications
- Understanding of modern AI application architectures, including RAG, vector databases, embeddings, model serving, and AI orchestration frameworks
- Experience with AWS/GCP, Docker & Kubernetes
Extracted from the job description · kept up to date automatically
Who this suits
This role suits experienced software engineers with over five years of experience in distributed systems, strong Python skills, and hands-on experience integrating LLMs or AI services into production. It is less ideal for junior developers or those without experience in cloud applications and microservice architectures.
Full job description
Original listing · kept for referenceWe're looking for a Senior Backend Engineer with a strong software engineering background, hands-on experience building production backend systems, and practical experience integrating AI and LLM technologies into real-world applications.
You will be a great fit if you enjoy building robust software systems that bring cutting-edge AI capabilities into production and solving complex engineering challenges at scale.
Moreover, you may have experience across roles such as Senior Backend Engineer, Senior Software Engineer, Platform Engineer, AI Infrastructure Engineer, Distributed Systems Engineer, or AI Application Engineer.
Job Description
• Design, build, and maintain scalable backend services that power our platform
• Develop APIs and microservices that integrate LLMs, computer vision models, and AI workflows into production systems
• Build scalable backend services that power AI-driven trade risk analysis, cargo inspection, and customs decision-support systems
• Collaborate closely with software engineers, data engineers, product teams, and customs-domain experts to turn AI capabilities into reliable production solution
• Contribute to software architecture decisions and engineering best practices across the platform
A day in the life
• Tackle complex, real-world customs inspection challenges where no “off-the-shelf” solutions exist
• Build AI systems that accelerate trade risk analysis and uncover fraudulent trade activities by connecting LLM-driven reasoning, structured trade and customs data, production software workflows
• Work closely with AI Engineers to operationalize machine learning models and LLM applications
• Design distributed services that process large volumes of customs declarations, documents, and cargo inspection data
• Build production-grade software with strong testing, monitoring, logging, and CI/CD practices
• Collaborate with AI Engineers, Computer Vision Engineers, Data Engineers to deliver end-to-end solutions
• Continuously improve system performance, reliability, and maintainability as AI capabilities evolve
You bring to the table
• Strong experience designing and building scalable distributed systems and microservice architectures
• Excellent Python development skills and hands-on experience using AI-assisted software development tools (e.g., Cursor, Claude Code, GitHub Copilot)
• Hands-on experience integrating LLMs or AI services into production applications
• Understanding of modern AI application architectures, including RAG, vector databases, embeddings, model serving, and AI orchestration frameworks
• Experience with observability, monitoring, logging, testing, and production debugging
• Strong software architecture and system design skills
• Ownership mindset with excellent problem-solving skills and the ability to drive technical initiatives independently
Experience & Education
• 5+ years of experience building large-scale backend or distributed software systems
• Proven experience delivering production-grade cloud applications
• B.Sc., M.Sc., or equivalent experience in Computer Science, Software Engineering, or a related field
Nice to have
• Experience with AWS/GCP, Docker & Kubernetes, customs/logistics applications
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- 5+ years of experience building large-scale backend or distributed software systems, Strong experience designing and building scalable distributed systems and microservice architectures, Excellent Python development skills and hands-on experience using AI-assisted software development tools, Hands-on experience integrating LLMs or AI services into production applications, Understanding of modern AI application architectures, including RAG, vector databases, embeddings, model serving, and AI orchestration frameworks