Delivers customer-facing AI agent solutions from technical discovery and proofs of concept through production rollout. The role requires 6+ years in a relevant technical discipline, strong architecture and developer communication skills, and experience with production AI, cloud, or related platforms.
200k – 250k/yr
Remote6+ YOESolutions Architecture
About the role
Responsibilities
Partner with account executives to scope evaluations, conduct technical discovery, and design customer-specific proofs of concept.
Serve as the technical authority during architecture reviews, security and infrastructure discussions, and competitive evaluations.
Co-architect and co-build production AI agents with customer engineering teams from prototype through rollout.
Help customers deploy and operate conversational agents, research agents, and multi-step workflows.
Run demos, trainings, and workshops for developer audiences.
Advise customers post-sale on architecture, best practices, and roadmap decisions, and identify expansion opportunities.
Surface field feedback to product teams and build reusable proofs-of-concept assets, cookbooks, and example code.
Contribute code upstream when it improves customer outcomes.
Requirements
6+ years in a relevant technical role such as solutions engineering, sales engineering, customer engineering, software engineering, or founding/product engineering.
Experience owning the technical thread in a sales cycle, including discovery, proofs of concept, architecture reviews, and competitive evaluations.
Ability to explain technical tradeoffs clearly, build trust with developer audiences, and translate technical work into customer decisions.
Track record of taking responsibility for outcomes rather than only making recommendations.
Bias toward action and willingness to solve unfamiliar problems.
Genuine interest in operating AI agents in production rather than only building demos.
Nice to Haves
Production deployment of AI agents, especially with LangChain, LangGraph, or similar frameworks.
Experience carrying a technical number or working alongside a sales team against pipeline goals.
Experience with LLM evaluation, observability, or guardrails.
Experience with cloud environments, containers, and basic Kubernetes concepts.
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