
Senior Backend Engineer
3 weeks ago
The Role: Systems Thinker+ AI-Driven Backend Architect
We're looking for a Senior Backend Engineer who lives and breathes web technologies and thrives at the intersection of cloud-native architecture, backend performance, and AI-enabled systems. At Studio93, we don't just build products—we craft experiences that are fast, scalable, and built for the future.
This is more than just a backend role. You'll play a foundational part in architecting intelligent systems, integrating large language models, and shaping the future of our tech stack. You'll collaborate with product-minded designers, frontend engineers, and founders to launch innovative products and AI features into the world.
If you're a systems thinker with strong opinions on clean architecture, efficient APIs, and LLM driven backend design let's talk.
What You'll Do- Architect and Build: Design, build, and maintain reliable backend systems and APIs using Python and Golang.
- Deploy at Scale: Architect and ship solutions on Google Cloud Platform, using Cloud Functions, Cloud Run, GKE, and other serverless/server-based strategies.
- Embed Intelligence: Build and scale RAG-based architectures, integrating LLMs with vector databases like PGVector, Pinecone, or Weaviate.
- Orchestrate AI Workflows: Leverage tools like LangChain and embedding models to support generative AI workflows.
- Infra as Code: Manage cloud infrastructure using Terraform or Google Cloud Deployment Manager.
- Process at Scale: Design RESTful APIs and implement asynchronous task queues using systems like Celery or Pub/Sub.
- Master the Data Layer: Work with both SQL (PostgreSQL) and NoSQL (Firestore) databases—building optimized access layers and schemas.
- Automate Everything: Contribute to CI/CD pipelines and build production-grade Dockerized services for rapid deployment and testing.
- 3–5+ Years of Experience in backend development using Python and Golang.
- Deep familiarity with GCP services and cloud-native deployment strategies (serverless and traditional).
- Strong experience with Infrastructure-as-Code tools like Terraform or Deployment Manager.
- Proven ability to design and scale Retrieval-Augmented Generation (RAG) systems in production environments.
- Working knowledge of vector DBs, embedding models, and frameworks like LangChain.
- Experienced in REST API design and asynchronous systems (e.g., task queues, Pub/Sub).
- Comfortable managing containerized environments (Docker) and CI/CD automation using GitHub Actions, Cloud Build, or Jenkins.
- Product-driven mindset with the ability to own projects end-to-end.
- Passion for AI and automation—experience using AI tools to accelerate development.
- Contributions to open-source projects or public technical writing.
- Experience mentoring engineers or leading backend projects.
- Familiarity with DevOps/SRE principles and monitoring tools.
- Massive Impact : Work on foundational backend systems powering intelligent apps used by thousands.
- High Autonomy : We don't micromanage—we expect and trust you to lead.
- AI at the Core : You won't just consume AI APIs; you'll shape how they work and integrate into products.
- Velocity & Innovation : Studio93 ships fast. We experiment, we learn, and we iterate constantly.
- Tight-knit Team : Collaborate closely with a small, driven team of founders, designers, and builders.
- Automate Everything: Contribute to CI/CD pipelines and build production-grade Dockerized services for rapid deployment and testing.
- Master the Data Layer: Work with both SQL (PostgreSQL) and NoSQL (Firestore) databases—building optimized access layers and schemas.
- Process at Scale: Design RESTful APIs and implement asynchronous task queues using systems like Celery or Pub/Sub.
- Infra as Code: Manage cloud infrastructure using Terraform or Google Cloud Deployment Manager.
- Orchestrate AI Workflows: Leverage tools like LangChain and embedding models to support generative AI workflows.
- Embed Intelligence: Build and scale RAG-based architectures, integrating LLMs with vector databases like PGVector, Pinecone, or Weaviate.
- Deploy at Scale: Architect and ship solutions on Google Cloud Platform, using Cloud Functions, Cloud Run, GKE, and other serverless/server-based strategies.
If this sounds like your kind of challenge, we'd love to meet you. Apply now and let's build the future together.
Seniority level- Seniority levelMid-Senior level
- Employment typeFull-time
- Job functionEngineering and Information Technology
- IndustriesIT Services and IT Consulting
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