Solutions Architect

About the role

Clarasight is seeking a Solutions Architect to own the design, delivery, and evolution of its most complex and high‑impact customer solutions. You will work hands‑on with enterprise clients, turning ambiguous travel challenges into concrete AI‑enabled solutions that deliver measurable results.

Key responsibilities

• Lead complex enterprise engagements from discovery through measurable value realization.
• Translate ambiguous customer problems into clear solution architectures, implementation plans, and success metrics.
• Act as a trusted advisor to leaders across travel, procurement, finance, IT, and sustainability.
• Rapidly prototype and iterate on solutions directly with customers to prove value early.
• Serve as a critical field‑to‑product feedback loop, shaping roadmap priorities and reusable capabilities.
• Partner closely with Sales, Product, Data, and Customer Success to drive retention, expansion, and long‑term impact.
• Work hands‑on with customer data, models, configurations, and analytics workflows to build proof‑of‑value implementations, dashboards, and planning models.
• Experiment with AI (LLMs, agents, workflow automation) to accelerate solution delivery and design AI‑augmented planning and decision‑support systems.
• Build custom integrations and workflows that don’t yet exist in the product, balancing speed and rigor as requirements, data, and tools evolve.

Required profile

• 5–8 years of experience in solution architecture, implementation consulting, or enterprise systems design.
• Comfort operating as a forward‑deployed problem solver, not just an advisor.
• Technically fluent and data‑oriented, understanding data models, metrics, transformations, and system workflows.
• Ability to query large datasets using SQL or similar tools.
• Exceptional communicator who can translate complex technical concepts into clear executive narratives.
• Thrives in early‑stage environments where ownership, judgment, and speed matter.

Required skills

• SQL querying of large datasets.
• AI technologies such as large language models and agents.
• Workflow automation and rapid prototyping.
• Design and implementation of custom integrations.