We are looking for an AI Solutions Architect to join our team and work on the design and delivery of advanced AI-driven solutions for our clients, with a strong focus on Generative AI.

Our mission is to help organizations translate business challenges into scalable, production-ready AI architectures, leveraging cloud platforms and modern AI capabilities such as LLMs, agentic systems, and intelligent automation.

This role sits at the intersection of technology and business, combining hands-on solution design with AI pre-sales activities. You will work closely with clients to shape AI strategies, define architectures, and guide implementation - ensuring solutions are both technically sound and aligned with business goals.

Position – how you’ll contribute

• Design end-to-end architecture for AI-driven solutions with a focus on Generative AI (LLMs, RAG, agents, automation)
• Engage in AI pre-sales activities such as:
• - Translate business requirements into AI solution proposals and architectures
• - Prepare architecture diagrams
• - Conduct client workshops, discovery sessions, and technical presentations
• Design scalable, secure, and cost-efficient AI architectures on cloud platforms (AWS, Azure, GCP)
• Define and oversee implementation of AI solutions such as RAG pipelines, vector search, intelligent systems, agents, and LLM integrations
• Be prepared to provide technical leadership and guidance to engineering teams during delivery
• Follow best practices for AI system design, governance, and responsible AI

Qualifications

Expectations – the experience you need

• 5+ years of experience in IT architecture, solutions architecture, or senior engineering roles OR 2+ years of experience specifically in AI/ML architecture
• Proven experience designing and delivering AI/ML or Generative AI solutions in production
• Strong understanding of LLMs, prompt engineering, RAG and Agentic architectures
• Hands-on experience or strong understanding of frameworks such as LangChain, LlamaIndex, or similar
• Experience architecting solutions on cloud platforms (AWS, Azure, or GCP)
• Strong knowledge of API design, system integration, and distributed architectures
• Experience with ML/AIOps practices (deployment, monitoring, lifecycle management)
• Proven ability to engage with stakeholders and translate business needs into technical solutio