Software Engineer II - Data Engineer

Job Summary

Build the software services that power products, platforms, and better business decisions. As a Software Engineer II, you'll develop scalable backend applications, APIs, integrations, and AI-enabled features using Python and cloud technologies.

You'll contribute to solutions from design through production, helping improve reliability, performance, security, and developer productivity. This is an opportunity to solve meaningful engineering challenges, grow your technical ownership, and collaborate with experienced engineers across the development lifecycle.

Here's a breakdown of what you'll do (not all of it, just the important stuff).

Responsibilities

• Design and build scalable backend services, REST APIs, integrations, and reusable software components using Python and, where relevant TypeScript.
• Develop data ingestion, transformation, service-to-service communication, and automation capabilities that support reliable product experiences.
• Contribute to AI-enabled features and use AI development tools responsibly to improve coding, testing, research, documentation, and delivery.
• Apply sound engineering practices across architecture, performance, security, testing, debugging, and maintainability.
• Deploy and operate services using AWS and CI/CD workflows, contributing to monitoring, troubleshooting, documentation, and continuous improvement.
• Partner with engineers and cross-functional colleagues through design discussions, code reviews, technical problem-solving, and knowledge sharing.

Requirements

• 3-5 years of professional experience building and delivering production software in an agile environment.
• Strong hands-on experience with Python and backend development, including APIs, integrations, or service-oriented applications.
• Experience working with cloud platforms, preferably AWS, and familiarity with deployment or CI/CD practices.
• Working knowledge of software design principles, testing, debugging, performance optimization, and secure development.
• Experience with SQL databases and Git-based development workflows.
• Practical understanding of AI or LLM concepts, such as generative AI, embeddings, context limits, hallucinations, or responsible AI tool use.
• Clear communication and a collaborative approach to technical problem-solving and delivery.

Nice-to-have

• Experience building data-intensive applications, ingestion services, distributed systems, or workflow-based solutions.
• Familiarity with containers, infrastructure as code, observability, automated quality practices, or MLOps.
• Exposure to TypeScript, React, LLM integrations, prompt engineering, retrieval-augmented generation, or other modern AI application patterns.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.