Senior Python Engineer

Summary

We are seeking a senior Python Backend Engineer to join a new internal project building an AI-driven tool to measure and improve Team engineering productivity. This role is focused on backend Python development combined with applied knowledge of large language models and AI practices to deliver production-quality internal tooling. The work will be collaborative with a distributed team and driven by a technically-oriented manager based in EST.

Responsibilities

• Design and implement backend services and APIs in Python for an internal AI-driven productivity tool.
• Develop and integrate AI/LLM components into backend workflows to support measurement and insights.
• Build reliable data pipelines and service integrations required by the AI tooling.
• Collaborate with the staff engineer lead and cross-functional contributors to define product requirements and technical approach.
• Iterate rapidly on prototypes and drive them to production-quality implementations.
• Troubleshoot, profile, and optimize backend systems and AI integrations for reliability and maintainability.
• Own end-to-end delivery for assigned components and provide guidance to less experienced engineers when needed.
• Communicate progress, trade-offs, and technical decisions clearly across distributed teams and stakeholders.

Requirements

• Senior-level backend engineering ownership: able to own a service end to end and support less experienced engineers.
• Expert proficiency in Python and its frameworks(Django/FastAPI).
• Experience working extensively with BigData workflows.
• Proficiency in AWS is a must have,  services including DynamoDB, Managed Services, Lambda functions; familiarity is highly recommended.
• Working experience on SQL databases such as Aurora and MySQL
• Working experience on key-value stores such as DynamoDB along with caching solutions such as Redis or ElastiCache.
• Demonstrated practical knowledge of large language models and AI practices as a required skill for integrating AI into backend solutions.
• Experience working on new, ambiguous projects with frequent changing requirements and the ability to operate independently.
• Comfort working on internal tools focused on engineering productivity and measuring engineering outcomes.