About Us
We are building next-generation AI-powered solutions that help users interact with large language models (LLMs) and deploy intelligent services seamlessly into their applications. Our suite includes a ChatGPT-style application and an AI integration platform that enables clients to deploy, scale, and manage AI modules and services efficiently.
We operate in cross-functional teams, deliver through microservices, and leverage cutting-edge technologies like LLMs, ingestion pipelines, Kubernetes, and ArgoCD, with frontend solutions in Angular, and backend services written in Kotlin and Python.
What You’ll Do
As a Senior Software Architect, you will be responsible for the design and architectural vision of our AI-driven applications. You'll lead the architecture of complex distributed systems, guide engineering teams, and ensure our solutions are robust, scalable, and maintainable.
Responsibilities
Design and evolve system architecture for our AI applications, including ingestion pipelines, LLM integration, and client deployment services.
Make high-level design decisions for microservices, data flow, APIs, and inter-system communication.
Provide architectural guidance to development teams, code reviews, and technical mentorship.
Collaborate with product owners, AI engineers, and DevOps to align architecture with business and technical goals.
Optimize system performance, scalability, and reliability.
Stay ahead of AI and software trends to integrate best practices in architecture and tooling.
Ensure security, compliance, and observability standards are met.
Drive architectural documentation and communication across cross-functional teams.
Requirements
Must-Have
Extensive experience in software engineering, with a proven track record as a lead or architect for large-scale systems.
Proficiency in Kotlin or Java is required.
Significant experience with Python, especially in the context of AI or data integration, is a strong advantage.
Strong knowledge of modern architectural patterns (e.g., microservices, event-driven systems, pub/sub messaging, domain-driven design).
Experience with LLMs or similar AI systems (e.g., prompt engineering, inference pipelines, fine-tuning, or embedding).
Deep understanding of system component design—including orchestration, APIs, databases, and deployment.
Experience with containerized environments (Docker/Kubernetes) and CI/CD pipelines; ArgoCD is a plus.
Familiarity with Angular or other frontend frameworks (for architectural integration).
Experience working in cross-functional agile teams.
