Solution Architect

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.