Python Engineer

Responsibilities:

• Develop and maintain scalable backend services and APIs using Python.
• Build and support backend functionality for AI/ML-enabled products, including integrations with ML models, AI services, and data-driven workflows.
• Design and implement reliable data processing, ingestion, and asynchronous backend flows.
• Work with cloud services and containerized environments to support scalable application delivery.
• Collaborate with cross-functional teams, including front-end developers, DevOps, product, and AI/ML specialists.
• Write clean, maintainable, and testable code following engineering best practices.
• Improve application performance, reliability, monitoring, and fault tolerance.
• Leverage AI-assisted development tools to accelerate delivery, improve code quality, and streamline repetitive engineering tasks.

Requirements:

• 4+ years of professional software engineering experience.
• Strong proficiency in Python and backend development.
• Experience designing and building APIs and backend services.
• Practical experience with AI/ML-related products, such as integrating AI services, ML models, data pipelines, or AI-driven features.
• Experience with relational and/or non-relational databases.
• Understanding of distributed systems, asynchronous processing, queues, or event-driven architecture.
• Hands-on experience with cloud services, preferably AWS.
• Practical hands-on experience with AI prompt engineering, leveraging Claude Code, Cursor, GitHub Copilot, or equivalent developer-AI tools.
• Solid understanding of LLM context design, tool integration, and code-generation workflows.

Nice to have:

• Experience with AWS services such as S3, API Gateway, Lambda, or SQS.
• Experience with Kubernetes in production environments.
• Experience designing data ingestion, replication, or ETL-style pipelines.
• Background in high-throughput backend services or large-scale data processing.
• Experience working closely with ML engineers or data teams.

Note:

The role description is intentionally high-level at this stage, as some project details are confidential. We will be happy to share more context during the interview process.