• Build and maintain data processing workflows using Prefect, GCP services, and REST APIs within a cloud-native microservices architecture.
• Write clean, well-tested code that adheres to team standards and passes CI/CD quality gates — Python proficiency is expected, with the ability to apply other languages as the problem requires.
• Actively use AI tools — including LLMs (Claude, Gemini, GPT) and AI coding assistants — to accelerate development, generate and validate code, and solve complex engineering problems.
• Participate in architecture and design reviews, contributing well-reasoned technical analysis and recommendations.
• Collaborate with senior engineers, product management, and QA to translate requirements into robust, testable implementations.
• Lead code reviews for junior engineers and provide constructive technical feedback.
• Investigate and resolve production bugs; contribute to improving system reliability and operational health.
• Stay current on AI frameworks, cloud-native tooling, and engineering best practices.
• 3–5 years of professional software engineering experience, with demonstrated ability to work independently on moderately complex features.
• Strong proficiency in Python; working knowledge of additional languages or frameworks appropriate to the task at hand.
• Experience building and maintaining data pipelines using workflow orchestration tools (Prefect, Airflow, or equivalent) and cloud data services.
• Hands-on experience with GCP and/or AWS, including cloud storage, serverless functions, and managed services.
• Demonstrated ability to use AI tools — such as Claude, ChatGPT, or Gemini — to accelerate development, debug problems, and produce higher-quality code faster.
• Solid understanding of software testing practices, CI/CD pipelines, and agile development methodologies.
• Working knowledge of containerization (Docker) and familiarity with Kubernetes or equivalent orchestration platforms.
• Good communication skills; comfortable collaborating across engineering and cross-functional teams.
Preferred Qualifications:
• Experience with microservices architecture and REST API development at scale.
• Familiarity with AI/ML frameworks or cloud-managed AI services (e.g., GCP Vertex AI, AWS Bedrock, LangChain).
• Exposure to prompt engineering, LLM integration, or agentic workflow design.
• Prior experience in an enterprise product engineering environment.
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