Solution Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Solution Architect based in United States.

This is a high-impact technical and client-facing role focused on designing and delivering enterprise-grade architectures that enable advanced data science and AI platforms to operate seamlessly within complex customer environments. You will act as a key bridge between customers, sales engineering, and internal product teams, translating real-world enterprise requirements into secure, scalable, and production-ready solutions. The role involves deep engagement with cloud, Kubernetes, identity, and data infrastructure, ensuring successful integration of a sophisticated AI/ML platform into regulated and large-scale IT ecosystems. You will also contribute directly to field innovation by building reusable integration patterns, reference architectures, and deployment frameworks. This is a highly collaborative position where technical depth, architectural thinking, and strong communication skills come together to drive customer success and product evolution.

• Design end-to-end solution architectures that integrate advanced AI and data platforms into enterprise environments, covering infrastructure, identity, security, and data systems.
• Lead the implementation of customer-specific integrations, including cloud-native deployments, Kubernetes-based environments, and ecosystem connectivity.
• Partner with sales engineering and account teams to scope solutions, build proofs of concept, and deliver tailored technical demonstrations for enterprise customers.
• Develop reusable architectural artifacts such as reference architectures, integration templates, and deployment runbooks to improve scalability and consistency across engagements.
• Collaborate with product and engineering teams to translate customer requirements, security constraints, and field feedback into actionable product enhancements.
• Support the enablement of internal teams by documenting best practices and sharing knowledge on integrations and field solutions.
• Continuously evaluate and apply emerging technologies across cloud, data, and AI/ML ecosystems to improve solution design and delivery.

Requirements:

• 5+ years of technical experience, including at least 1+ year in a client-facing solutions, consulting, or pre-sales engineering role.
• Strong experience designing and deploying solutions in complex enterprise environments, ideally including regulated industries.
• Hands-on expertise with Kubernetes (EKS, AKS, or GKE) and containerized application architectures.
• Experience with at least one major cloud platform (AWS, Azure, or GCP) in production environments.
• Strong understanding of Linux systems and distributed computing concepts; experience with Spark, Hadoop, or Dask is a plus.
• Experience with APIs, system integrations, identity and access management (SAML/OIDC, Keycloak), and CI/CD pipelines.
• Programming experience in Python or R, with additional exposure to Bash or Terraform considered a plus.
• Ability to translate security, compliance, and governance requirements into robust, scalable architecture designs.
• Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Experience with AI/ML platforms or data science tooling is highly desirable.

Benefits:

• Competitive compensation package including base salary range of $180,000–$220,000 USD, with potential additional bonus or equity components.
• Fully remote work flexibility within the United States.
• Opportunity to work on cutting-edge AI and data science platforms used by leading global organizations.
• High-impact role engaging directly with enterprise customers and shaping real-world AI/ML deployments.
• Exposure to modern cloud, Kubernetes, and distributed data architectures at scale.
• Collaborative, innovation-driven environment with strong emphasis on learning and technical growth.
• Opportunity to influence product direction through direct feedback from customer implementations.