AI / ML Solution Architect

Job description

ABOUT THE ROLE

In this role, you will design and deliver enterprise AI/ML solutions for client engagements, with a primary focus on the Middle East and Central Asia. You will shape scalable and secure architectures across on-premises and hybrid environments, working with enterprise customers, technology partners, and delivery teams from use-case definition through production.

RESPONSIBILITIES

- Design end-to-end AI/ML solution architectures aligned with enterprise business, data, security, and infrastructure requirements

- Lead AI initiatives from use-case definition and technical discovery through architecture, implementation, deployment, and transition to production

- Define architectures for Generative AI, LLM, RAG, AI agents, and intelligent automation using NVIDIA and other enterprise technologies

- Recommend appropriate AI technologies, frameworks, deployment approaches, and infrastructure sizing, including GPU-based environments

- Collaborate with enterprise customers, technology partners, engineers, data scientists, and infrastructure teams throughout the solution lifecycle

- Integrate AI solutions with enterprise data platforms and technologies such as NVIDIA AI Enterprise, Cisco AI Defense, Splunk, IBM watsonx, and ServiceNow

- Guide implementation teams to ensure scalability, security, performance, reliability, maintainability, and operational readiness

- Support technical discovery, customer workshops, solution estimation, and proposal development while applying AI engineering and MLOps best practices

REQUIREMENTS

- 2+ years of experience as a Solution Architect designing complex AI/ML solutions and 4+ years of technical leadership experience in Machine Learning or Data Science

- Strong experience designing and delivering enterprise AI/ML solutions, including Generative AI, LLMs, RAG, and AI agent architectures

- Strong knowledge of on-premises and hybrid infrastructure, Kubernetes-based environments and/or VMware, and cloud platforms such as Azure, AWS, or Google Cloud

- Strong understanding of MLOps, model deployment, monitoring, AI lifecycle management, Python, and modern AI/ML frameworks

- Experience with NVIDIA AI Enterprise, NVIDIA GPU infrastructure, or related NVIDIA AI technologies would be an advantage

- Experience delivering AI solutions in the Middle East or Central Asia, regulated enterprise environments, or in collaboration with technology partners and OEMs would be an advantage

- Strong analytical, problem-solving, communication, and stakeholder management skills, with the ability to lead technical discovery and solution-design discussions with enterprise customers

- Availability to travel up to 2–3 weeks per month, primarily for customer and partner engagements