CodeTiburon is looking for a Founding AI Platform Architect (Python & Kubernetes) to become one of the first key engineers building a next-generation AI platform together with one of our long-term product partners.
Greenfield Product • Founding Engineering Team • Python • Kubernetes • LLMs • AI Agents • Knowledge Graphs • AWS
This is a rare opportunity to shape the technical foundation of a greenfield AI product from its earliest stages and have a lasting impact on its architecture, scalability, and evolution.
The Project
We're building a next-generation AI platform that combines LLMs, AI agents, knowledge graphs, and vector search to create reliable, production-grade AI systems.
The platform powers intelligent assistants capable of solving complex business problems through advanced orchestration, retrieval, and structured reasoning. Behind the scenes, we're building the distributed infrastructure that enables model inference, AI workflows, knowledge graph integrations, evaluation pipelines, and multi-tenant SaaS capabilities.
As part of our long-term engineering partnership, you'll become a founding member of the engineering team responsible for designing and building this platform from the ground up.
The Role
This is a highly autonomous, hands-on architecture role where you'll combine backend engineering, cloud infrastructure, and AI platform design.
You'll architect the platform, build core backend services in Python, design and evolve the Kubernetes infrastructure, and transform cutting-edge AI research into reliable, scalable production systems.
Working directly with AI researchers, domain experts, and product stakeholders, you'll translate ambitious ideas into production-ready capabilities while shaping the long-term technical direction of the platform.
If you enjoy building systems from first principles, making architectural decisions, and taking full ownership of complex engineering challenges, you'll feel at home here.
Responsibilities
- Design and evolve the overall architecture of the AI platform.
- Build scalable backend services and APIs using Python.
- Design, deploy, and operate production workloads on Kubernetes.
- Architect data storage, retrieval, and messaging solutions.
- Build the infrastructure powering AI agents, LLM inference, RAG pipelines, and knowledge graph integrations.
- Design integrations with external SaaS platforms and enterprise systems.
- Establish engineering standards, architectural principles, and development best practices.
- Evaluate and introduce technologies that improve scalability, reliability, security, and developer productivity.
- Collaborate closely with AI researchers, domain experts, and product stakeholders to bring new capabilities into production.
- Troubleshoot complex production issues across application, infrastructure, and Kubernetes layers.
What You'll Own
- The overall architecture of the AI platform.
- Technology selection and key architectural decisions.
- Production infrastructure running on Kubernetes.
- Platform scalability, reliability, observability, and performance.
- The technical foundation for future AI capabilities.
Requirements
Must Have
- Extensive experience designing and building production-grade backend systems in Python.
- Strong hands-on expertise with Kubernetes, including deploying, scaling, operating, and troubleshooting production workloads.
- Proven experience designing distributed systems, microservices, and cloud-native architectures.
- Strong architectural thinking and the ability to make independent technical decisions across application design, infrastructure, data storage, and system integration.
- Solid experience with PostgreSQL and designing scalable data models.
- Experience designing and building scalable REST APIs and integrating external SaaS platforms and enterprise systems.
- Strong understanding of asynchronous and event-driven architectures using technologies such as RabbitMQ, Kafka, or similar.
- Experience building secure, observable, resilient, and maintainable production systems.
- Demonstrated ability to take technical ownership and deliver complex projects from concept to production with a high degree of autonomy.
- Strong communication skills and experience collaborating directly with product stakeholders, domain experts, and engineering teams.
- Professional English proficiency (C1 or higher).
Nice to Have
- Experience building AI platforms or LLM-powered applications.
- Experience with LangGraph, LangChain, CrewAI, or other AI agent orchestration frameworks.
- Experience designing and implementing RAG pipelines.
- Experience with vector databases and semantic search technologies such as pgvector, Milvus, or Weaviate.
- Experience integrating knowledge graphs into production systems.
- Familiarity with AI model serving and inference infrastructure.
- Experience with GitOps, ArgoCD, Helm, or Kubernetes Operators.
- Experience with AWS, Azure, or GCP.
- Experience building multi-tenant SaaS platforms.
- Contributions to open-source projects, technical publications, or conference talks.
This Role Is for You If...
- You enjoy building products from scratch rather than maintaining legacy systems.
- You naturally think in terms of architecture, scalability, and long-term maintainability.
- You prefer technical ownership over simply implementing backlog tasks.
- You're comfortable making architectural decisions in environments with evolving requirements.
- You enjoy collaborating directly with AI researchers, domain experts, and product leaders.
- You value clean architecture, pragmatic engineering, and continuous learning.
- You're excited by the opportunity to build the technical foundation of next-generation AI products.
This Role May Not Be the Right Fit If...
- You prefer working from detailed specifications rather than defining technical direction.
- You're looking primarily for feature implementation instead of architecture ownership.
- You prefer working exclusively on application code without infrastructure responsibilities.
- You aren't comfortable making independent technical decisions with a high degree of autonomy.
Why Join Us
- Build a greenfield AI platform from day one.
- Become one of the first engineers shaping the product and its architecture.
- Work at the intersection of AI, distributed systems, and cloud infrastructure.
- Collaborate directly with AI researchers and domain experts.
- Own major architectural decisions with real product impact.
- Solve technically challenging problems instead of implementing routine backlog tasks.
- Help define the engineering culture, standards, and long-term technical vision of the platform.
If this opportunity matches your experience and ambitions, we'd love to hear from you. Please send us your CV.
Every application is carefully reviewed. Candidates whose experience and background best match the role will be contacted regarding the next steps.
