Build and deploy production AI agents alongside customer engineering teams, leading technical evaluations, architecture, and post-sale advisory work. The role requires 6+ years of relevant technical experience, strong Python and JavaScript skills, and hands-on experience with LLM-powered applications.
150k – 250k/yr
Remote6+ YOESolutions Architecture
About the role
Responsibilities
Co-architect and co-build production AI agents with customer engineering teams.
Own the technical win in pre-sales by designing proofs of concept, answering deep technical questions, and guiding evaluations.
Help customers deploy and operate agent-based applications, including conversational agents, research agents, and multi-step workflows.
Advise customers post-sale on architecture, best practices, and roadmap-level decisions.
Run technical demos, trainings, and workshops for developer audiences.
Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers.
Occasionally contribute code upstream when it meaningfully improves customer outcomes.
Travel to customers up to 40% of the time.
Requirements
6+ years in a relevant technical role, such as software engineering, customer engineering, solutions engineering, founding engineering, or product engineering; startup or scale-up experience is preferred.
Strong Python, JavaScript, and systems fundamentals.
Experience designing agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling.
Comfort working directly with customers during proofs of concept, architecture reviews, and technical evaluations.
Ability to explain technical tradeoffs clearly and build trust with developer audiences.
Ownership of outcomes, not just recommendations.
Bias toward action and comfort figuring things out as work evolves.
Interest in operating AI agents in production, not just building demos.
Nice to Have
Experience deploying AI agents in production, especially using LangChain, LangGraph, or similar frameworks.
Experience with LLM evaluation, observability, or guardrails.
Experience with cloud environments, containers, and basic Kubernetes concepts.
Experience shipping and operating production software under real-world constraints.
Compensation and Benefits
Annual OTE range: $150,000–$250,000 USD.
Compensation includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
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