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Software Developer, Backend Developer, Software Engineer

Job in San Diego, San Diego County, California, 92189, USA
Listing for: Wonderist Agency
Full Time position
Listed on 2026-05-19
Job specializations:
  • Software Development
    Backend Developer, Software Engineer
Salary/Wage Range or Industry Benchmark: 90000 - 120000 USD Yearly USD 90000.00 120000.00 YEAR
Job Description & How to Apply Below

Job Description

As a Software Developer at Wonderist, you’ll help build and evolve the in‑house platforms and automations that make our agency run — the systems our clients rely on for integrated marketing, the internal tools our team uses to deliver great work, and the AI‑powered capabilities we’re layering on top of both. You’ll work end‑to‑end: shaping architecture, writing production code, integrating third‑party services, designing data models, and shipping things that real teammates and real clients use the next day.

Essential

Functions
  • Platform Engineering: Maintain and extend our multi‑tenant web application — the system that powers integrations and CRM capabilities for our clients. Make thoughtful architecture decisions around tenancy, scaling, and performance as our footprint grows.
  • Full‑stack Application Development: Design, build, and ship production web applications. Own the full lifecycle—architecture through deployment—and contribute to our front‑end component system.
  • Data and Integrations: Design and maintain the databases, sync flows, webhooks, and background jobs that move information between our systems and the third‑party platforms our clients depend on (telephony, messaging, CRM, marketing analytics, scheduling, and practice management tools, among others). Build integrations that are observable, idempotent, and resilient to partial failures.
  • AI‑powered Systems: Help integrate large language models, embeddings, and vector search into real business workflows—internal copilots, intelligent reporting, classification and prediction, and agentic automations. Build the data foundations that make the rest of the company’s information actually usable by AI.
  • Automation and Tooling: Replace fragile no‑code automations with reliable, well‑tested Python services where it matters. Build the internal tooling and dashboards that help client‑facing teams move faster and serve clients better.
  • Reliability and Quality: Establish and maintain the testing, monitoring, logging, and CI/CD practices that let us deploy with confidence. Document what you build so the rest of the team—and future‑you—can pick it up.
Core Competencies
  • Engineering Fundamentals: Strong grasp of software design, clean code, testing, version control, code review, and shipping production systems. Comfortable navigating an existing codebase—not just starting greenfield projects.
  • Python and a Modern Web Framework: Production experience building and shipping web applications in Python. Our current platform is Django, and ramping up on Django quickly is part of the job; equivalent experience in another mature web framework plus a real willingness to learn Django is acceptable.
  • Relational Databases: Solid command of a production‑grade relational database (we use Postgre

    SQL): schema design, indexing, query optimization, migrations, and debugging real performance issues. Awareness of scaling strategies—read replicas, partitioning, sharding—even if you haven’t implemented all of them yourself.
  • Asynchronous and Integration‑heavy Systems: Experience designing systems driven by webhooks, background jobs, and third‑party APIs. Comfortable with task queues, retries, idempotency, and the failure modes that come with distributed systems.
  • Cloud Deployment and Dev Ops: Comfortable with Git workflows, containerization (Docker), CI/CD, and deploying to a managed cloud platform (Heroku, AWS, GCP, Azure, or similar).
  • APIs: Working knowledge of designing and consuming REST APIs, plus the operational pieces around them (auth, rate limiting, error handling, observability).
  • Practical AI/ML

    Experience:

    Hands‑on experience integrating LLM APIs (OpenAI, Anthropic, or similar) into real applications, plus a working understanding of embeddings, retrieval‑augmented generation, and prompt design. Depth here is welcome but not required on day one—interest and momentum matter more than résumé check marks.
  • Product Mindset: You can sit with non‑technical teammates, understand what they actually need, and translate that into systems that fit the business. You ship things that work for the people who use them.
Personality Musts

Our perfect fit is someone who is a problem…

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