Backend Engineer

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

• 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 Postgre
  
  SQL) 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