CodeTiburon is looking for a Founding AI Platform Architect (Python & Kubernetes) to join our team and work closely with one of our long-term clients. About 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 key member of the core team responsible for designing and building this platform from the ground up. About the role We’re looking for an AI Platform Architect (Python & Kubernetes) who enjoys designing complex distributed systems and taking full ownership of technical decisions.
This is a highly autonomous, hands-on architecture role. You’ll design the platform architecture, build core backend services in Python, define and evolve the Kubernetes infrastructure, and transform AI research into reliable, scalable production systems.
You’ll work directly with AI researchers, domain experts, and product stakeholders, turning complex ideas into production-ready solutions while shaping the long-term technical direction of the platform.
If you’re passionate about building systems from first principles, enjoy solving infrastructure challenges at the intersection of AI and distributed systems, and want to own architecture rather than simply implement backlog tasks, you’ll feel at home here.
Responsibilities * Own the architecture of a modern AI platform built around Python, Kubernetes, LLMs, and distributed systems. * Design and implement scalable backend services, APIs, and platform components from concept to production. * Design, deploy, and operate production workloads on Kubernetes, ensuring scalability, reliability, and observability. * Architect data storage and retrieval solutions using PostgreSQL, pgvector, and other technologies where appropriate. * Design event-driven integrations with external platforms, SaaS products, and enterprise systems. * Build the infrastructure that powers AI agents, LLM inference, retrieval pipelines, and knowledge graph integrations. * Evaluate and introduce new technologies, frameworks, and architectural patterns that improve the platform. * Collaborate directly with AI researchers, domain experts, and product stakeholders to transform ideas into production-ready systems. * Drive technical decisions, establish engineering standards, and ensure long-term maintainability of the platform. * 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. * Scalability, reliability, and performance of the platform. * 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. * Proven ability to make independent architectural decisions across application design, infrastructure, data storage, and system integration. * Strong understanding of PostgreSQL and experience designing data models and selecting appropriate persistence technologies for different workloads. * Experience designing and building scalable REST APIs and integrating with third-party SaaS platforms and enterprise systems. * Solid understanding of asynchronous and event-driven architectures, including messaging systems such as RabbitMQ, Kafka, or similar technologies. * Experience building secure, reliable, observable, and maintainable production systems. * Demonstrated ability to take technical ownership and deliver complex projects from concept to production with a high degree of autonomy. * Experience collaborating directly with product stakeholders, domain experts, and engineering teams to translate business problems into technical solutions. * 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 with vector databases and semantic search technologies (e.g. pgvector, Milvus, Weaviate). * Experience designing and implementing RAG pipelines. * Experience integrating knowledge graphs into AI applications. * Familiarity with AI model serving and inference infrastructure. * Experience with GitOps, ArgoCD, Helm, or Kubernetes Operators. * Experience with cloud platforms such as AWS, Azure, or GCP. * Experience building multi-tenant SaaS platforms. * Contributions to open-source projects or technical publications.
This Role Is for You If... * You enjoy building systems from scratch rather than maintaining legacy code. * You naturally think in terms of architecture, scalability, and long-term maintainability. * You like making technical decisions and taking ownership of their outcomes. * You’re comfortable working with ambiguity and turning high-level ideas into production-ready systems. * You enjoy collaborating directly with AI researchers, product stakeholders, and domain experts. * You value clean architecture, pragmatic engineering, and continuous learning. * You’re excited by the challenge of building the technical foundation of next-generation AI products.
This Role May Not Be the Right Fit If... * You prefer well-defined backlog tasks over shaping technical direction. * You expect detailed specifications before starting implementation. * You enjoy working exclusively on application code without infrastructure responsibilities. * You’re looking for a role focused primarily on feature development rather than platform engineering and architecture.
If this sounds like you and your experience aligns with most of the qualifications above, we’d love to hear from you. Please send us your CV.
Thank you for your interest. Each application is carefully reviewed, and candidates whose experience and background best align with the role will be contacted regarding the next steps.
