Principal Engineer Lead

• Design and build robust, secure, and scalable backend services for reporting, analytics, and data delivery.
• Develop across Node.js, Python, .NET, and SQL, supporting data pipelines for internal and external stakeholders.
• Operate within a modern cloud environment, leveraging services such as Lambda, Athena, Glue, DynamoDB, Redshift, and S3.
• Participate in architecture reviews, propose improvements, and proactively identify technical debt or performance bottlenecks.
• Lead AI-native development workflows using LLM-based tools (Claude, Cursor, etc.) for rapid prototyping, iteration, and system-level design.
• Define architectural patterns and guardrails for AI-assisted backend systems, including prompt management, cost controls, and evaluation frameworks.
• Coach and mentor engineers in AI-first workflows, fostering team fluency in prompt-driven development.
• Design and maintain shared AI resources like prompt libraries and reusable workflows to raise team productivity.
• Collaborate cross-functionally with product owners, engineers, data scientists, and customer teams to define and deliver high-impact solutions.
• Own and continuously improve team delivery flow, including managing work-in-progress, ensuring shippable outcomes, and removing bottlenecks.

• 8+ years of backend development experience, building and maintaining production systems.
• Strong expertise in cloud-based architectures, APIs, CI/CD pipelines, and containerized environments.
• Deep knowledge of AWS services (Lambda, DynamoDB, API Gateway, S3, CloudFormation) or equivalent cloud platforms.
• Hands-on experience with AI coding tools and AI-first development workflows.
• Skilled in Node.js, Python, and/or .NET, with experience in relational and NoSQL databases and distributed data pipelines.
• Experience with serverless environments, cloud-native application design, and large-scale data processing frameworks (PySpark, Glue, etc.).
• Strong judgment in evaluating AI-generated code for correctness, performance, and reliability.
• Track record of applying AI to solve real product or data problems, not just internal tooling.
• Strong communicator and collaborator, capable of working in fully remote, asynchronous teams.
• Self-directed, able to work autonomously, and comfortable acting as a hands-on technical lead.
• Bachelor's degree in Computer Science, Engineering, or related field preferred; strong portfolio and demonstrated ability valued.

Preferred:

• Startup or early-stage experience with ownership of large technical areas.
• Familiarity with AI/ML infrastructure, including model serving, RAG architectures, evaluation pipelines, or vector databases.
• Passion for education or improving learning outcomes through technology.