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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