Backend Engineer

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What You'll Do

• Partner with the Machine Learning team to design and implement scalable solutions that meet customer-specific requirements
• Work directly with clients to gather requirements, provide technical guidance, and serve as the post-go-live ML point of contact
• Develop custom APIs and backend services to enable seamless integration with customer environments
• Troubleshoot and resolve complex technical issues, acting as the technical liaison between customers and the engineering team
• Deliver small, targeted features to unblock high-priority edge cases and resolve customer tickets
• Partner closely with the ML team on inference/data pipeline issues, adding validation and guardrails where needed
• Collaborate with Product, Engineering, Customer Success, and Sales to refine features, improve customer experience, and produce clean documentation for smooth handover
• Contribute to continuous improvement of backend architecture and services, incorporating customer feedback and industry trends
• Build and maintain self-service tooling to enable non-engineers to diagnose and resolve common issues

Requirements

• Proven experience in Python-based backend development; exposure to frontend technologies (particularly React) is desirable
• Skilled in troubleshooting complex production issues, ensuring rapid resolution and system reliability
• Track record of delivering technical solutions and providing expert guidance to clients in professional services or consulting settings
• Ability to design and build scalable, cloud-based systems and APIs that integrate with client systems
• Experience with database technologies (preferably PostgreSQL) and backend frameworks such as FastAPI
• Knowledge of modern AI tools such as Cursor
• Hands-on experience working with LLMs and prompt engineering
• Strong communication skills, able to convey complex technical concepts to both technical and non-technical stakeholders
• Problem-solving mindset with a passion for customer satisfaction and delivering quality solutions
• Experience with containerization and deployment practices (Docker, Kubernetes, AWS/Azure/GCP) is a plus
• Demonstrated ability to balance technical excellence with business requirements and time constraints

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