AI / ML Solution Architect

Location: Bulgaria or Poland; remote/office work format

Company

hirify.global delivers engineering and technology solutions for enterprise customers.

What you will do

• Design end-to-end AI/ML solution architectures aligned with business, data, security, and infrastructure requirements.
• Lead AI initiatives from use-case definition and technical discovery through implementation, deployment, and production transition.
• Define Generative AI, LLM, RAG, AI agent, and intelligent automation architectures using NVIDIA and other enterprise technologies.
• Recommend AI technologies, frameworks, deployment approaches, and infrastructure sizing, including GPU-based environments.
• Collaborate with enterprise customers, technology partners, engineers, data scientists, and infrastructure teams.
• Guide implementation teams on scalability, security, performance, reliability, maintainability, and operational readiness.

Requirements

• At least 2 years of experience as a Solution Architect designing complex AI/ML solutions and at least 4 years of technical leadership experience in Machine Learning or Data Science.
• Strong experience with enterprise AI/ML solutions, including Generative AI, LLMs, RAG, and AI agent architectures.
• Knowledge of on-premises and hybrid infrastructure, Kubernetes and/or VMware, and Azure, AWS, or Google Cloud.
• Understanding of MLOps, model deployment, monitoring, AI lifecycle management, Python, and modern AI/ML frameworks.
• Strong analytical, problem-solving, communication, and stakeholder management skills.
• Availability to travel up to 2–3 weeks per month for customer and partner engagements.

Nice to have

• Experience with NVIDIA AI Enterprise, NVIDIA GPU infrastructure, or related NVIDIA AI technologies.
• Experience delivering AI solutions in the Middle East or Central Asia, regulated enterprise environments, or with technology partners and OEMs.

Culture & Benefits

• Work format supports remote or office-based work.
• Engagement with enterprise customers, technology partners, and delivery teams.
• Opportunities to work across the full AI solution lifecycle, from discovery to production.