Sr. AI Solutions Engineer
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Looking for a solutions engineer job in Seattle? Choose from 12 open roles at 4 employers. Explore real salary data and skills breakdown across remote, hybrid and on-site roles.
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In the week to 27 September, 12 solutions engineer roles were open in Seattle at 4 employers. 3 new roles were posted during the week. Of the roles that say how they work, 8% are remote or hybrid.
Among the solutions engineer roles listed on the board for Seattle, the vast majority are at a lead level, with a small share at manager level. A little over a third of the openings were posted around two months ago, and roughly equal portions arrived within the last week, the last month, and the last three weeks, suggesting a modest but ongoing pace of new listings. All of the roles listed here sit within a handful of employers, so the active hiring pool is concentrated rather than spread broadly. AWS appears in most role descriptions, and a good portion mention large language models, fine-tuning, and publications, pointing to teams that work at the intersection of cloud infrastructure and applied AI. There is not enough weekly history yet to describe how volumes have changed over time.
Figures are measured every Monday.
Solutions engineers sit between technical product teams and customers or partners, translating complex technology into working implementations and making sure deployments succeed in real environments. The work typically involves scoping customer needs, building proof-of-concept integrations, and supporting pre-sales or post-sales technical conversations. In a city where major cloud and software companies maintain large engineering campuses — Amazon's headquarters spans the South Lake Union neighbourhood and Microsoft's is close by in Redmond — solutions engineers often work inside or alongside platform teams rather than at independent consultancies. Research institutions such as Ai2 and the University of Washington's Paul G. Allen School also contribute to an environment where applied AI work is common, which may explain why AI-focused capabilities appear frequently in local role descriptions.
Cloud fluency, particularly with AWS, appears in most descriptions, making it the clearest technical foundation to demonstrate. Large language models, fine-tuning, and publication experience are each mentioned in roughly a third of descriptions, suggesting that some teams expect candidates to engage with research as well as engineering. Agents, evaluation, and RAG appear in a smaller share, and Python, PyTorch, TensorFlow, and Kubernetes are each mentioned in a minority of descriptions. Skills figures reflect mentions across descriptions, not universal requirements.
All of the roles listed here that state a work mode specify on-site work; none list hybrid or remote arrangements. Candidates should expect to be present at an employer's Seattle location. Given the concentration of roles among a small number of large employers with established campuses, on-site expectations are consistent with the norm for this kind of role in this market.
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