AI-Native Fullstack SDE

TL;DR We're looking for an AI-Native Fullstack Software Development Engineer to join our fast-moving, high-impact team. In this hands-on role, you'll contribute across our backend (Python/Django) and frontend (JavaScript/TypeScript, Vue.js/Nuxt) stacks, working closely with senior engineers and product stakeholders to ship features, improve system performance, and help scale our platform — with AI-assisted development as a core part of how you work, not a side experiment. This role is ideal for someone with 2–5 years of professional experience and a strong foundation in fullstack development, CI/CD best practices, and cloud infrastructure (particularly GCP), who has fluently integrated coding agents, LLM APIs, and AI-powered tooling into their daily workflow. Ambitious, detail-oriented developers who treat AI as a force multiplier — and are eager to shape the future of our product — should apply by sending a statement of interest and resume to talent@bullwhip.io.

What You’ll Do

As a Principal SDE at Bullwhip, your role will span the following:

Backend & Data Engineering

• Build and maintain Python/Flask/Django services that support performance analytics, reporting, and client integrations.
• Work with Postgres, BigQuery, and Pub/Sub to build reliable and scalable batch and real-time data pipelines.
• Develop and manage data pipelines for in-house and client data at scale.
• Lead new client integration / onboarding efforts, including improving data structure normalization and automation where helpful.
• Contribute to data validation and ingestion logic to ensure data quality across systems.
• Support integrations with tools like GCP Workflows, Cloud Run Jobs, and AlloyDB as the stack evolves.

Frontend Development

• Build and maintain frontend Node/JS services that support realtime analytics, yield optimization and attribution.
• Develop frontend components for our Vue.js/Nuxt-based analytics application (Beacon).
• Contribute to browser-based tools (e.g., Chrome Extensions) for on-page analytics, DOM interaction, and URL rewriting.
• Optimize performance and maintain compatibility across diverse client environments.

Infrastructure & CI/CD

• Contribute to CI/CD workflows using GitHub Actions, Docker, and GCP-native tools.
• Help automate client onboarding workflows and repetitive integration tasks.
• Participate in performance monitoring, logging, and observability improvements.

Team Collaboration

• Work closely with senior engineers, product managers, and client-facing teams to deliver features and debug production issues.
• Follow modern development practices and contribute to internal documentation.
• Learn and grow under the mentorship of Principal and Staff-level engineers.

AI-Native Development

Successful candidates will have a demonstrated track record of the following competencies:

• Using coding agents (Claude Code, Cursor, Copilot, or equivalent) as a daily part of feature development, debugging, refactoring, and code review.
• Building internal tooling, automations, and prototypes that leverage LLM APIs (Anthropic, OpenAI, etc.) where they meaningfully accelerate the team or product.
• Applying strong judgment on when AI assistance adds leverage vs. when it introduces risk — review and own all generated code as if you wrote it yourself.
• Contributing to internal AI workflow conventions: prompt patterns, agent configurations, MCP integrations, and repo-level context (CLAUDE.md, .cursorrules, etc.).
• Helping evaluate and adopt emerging AI dev tools, and share learnings with the rest of engineering.

Qualifications

Core Experience

• 2–5 years of professional experience as a fullstack or backend software engineer.
• Strong proficiency in Python/Django and Node/JavaScript/TypeScript.
• Experience with at least one modern frontend framework—Vue.js, Nuxt, or React.
• Working knowledge of SQL and experience with Postgres and/or BigQuery.
• Solid fundamentals in systems design, data structures, and version control (Git).
• Demonstrated fluency with AI coding tools (Claude Code, Cursor, Copilot, Windsurf, or similar) in real production work — not just experimentation.
• Comfort calling LLM APIs directly and reasoning about tradeoffs (model choice, context windows, structured outputs, tool use, cost/latency).

Cloud & DevOps

• Experience deploying to or building on Google Cloud Platform (GCP).
• Exposure to Cloud SQL, Pub/Sub, BigQuery, GCS, and IAM.
• Familiarity with CI/CD pipelines and containerization tools like Docker.

Problem Solving & Communication Skills

• Proven ability to troubleshoot bugs, track down root causes, and write maintainable solutions.
• Effective communicator—able to document decisions clearly and collaborate across functions.

Bonus Points

• Experience with website event tracking, or in-browser SDKs.
• Exposure to affiliate marketing systems or digital advertising pipelines.
• Experience building or maintaining Chrome Extensions.
• Familiarity with tools like Airflow, Datastream, or large-scale