Job VC
Python Engineer
Technologies
Description
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.
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.