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
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Design and evolve system architecture for our AI applications, including ingestion pipelines, LLM integration, and client deployment services.
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Make high-level design decisions for microservices, data flow, APIs, and inter-system communication.
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Provide architectural guidance to development teams, code reviews, and technical mentorship.
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Collaborate with product owners, AI engineers, and DevOps to align architecture with business and technical goals.
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Optimize system performance, scalability, and reliability.
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Stay ahead of AI and software trends to integrate best practices in architecture and tooling.
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Ensure security, compliance, and observability standards are met.
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Drive architectural documentation and communication across cross-functional teams.
Requirements
Must-Have
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Extensive experience in software engineering, with a proven track record as a lead or architect for large-scale systems.
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Proficiency in Kotlin or Java is required.
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Significant experience with Python, especially in the context of AI or data integration, is a strong advantage.
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Strong knowledge of modern architectural patterns (e.g., microservices, event-driven systems, pub/sub messaging, domain-driven design).
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Experience with LLMs or similar AI systems (e.g., prompt engineering, inference pipelines, fine-tuning, or embedding).
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Deep understanding of system component design—including orchestration, APIs, databases, and deployment.
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Experience with containerized environments (Docker/Kubernetes) and CI/CD pipelines; ArgoCD is a plus.
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Familiarity with Angular or other frontend frameworks (for architectural integration).
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Experience working in cross-functional agile teams.