Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Deployed Architect, Post-Sales (AI): Designing and deploying production-grade AI infrastructure and agent systems for enterprise customers with an accent on Kubernetes, cloud platforms, infrastructure as code, and multi-agent architectures. Focus on building highly available and secure deployments, evaluating and optimizing agents, and translating complex customer requirements into reliable implementations.
Location: Remote; listed locations are Los Angeles, Denver, Salt Lake City, and Seattle
Company
LangChain builds open-source frameworks and a platform for building, evaluating, deploying, and operating intelligent agents at scale.
What you will do
- Design scalable, highly available, and secure infrastructure for enterprise AI platform deployments, including compute, storage, networking, and security.
- Architect Kubernetes environments, multi-region high-availability and disaster-recovery strategies, enterprise integrations, and CI/CD pipelines.
- Build production multi-agent systems with LangChain and LangGraph, including state management, tool integrations, API design, and error handling.
- Design evaluation frameworks, optimize prompts through A/B testing, and guide agent deployment and operations.
- Lead technical maturity assessments and infrastructure audits for enterprise customers.
- Partner with customers, Engagement Managers, and Product and Engineering teams to define requirements and guide implementation.
Requirements
- 7+ years in hands-on, technical, customer-facing roles such as Solutions Architect or Forward Deployed Engineer.
- 3+ years designing and deploying production infrastructure on GCP, AWS, or Azure, with strong Kubernetes experience including cluster design, autoscaling, and multi-zone deployments.
- Experience with Terraform, Helm, GitOps, databases, high availability, disaster recovery, networking, security, observability, and CI/CD.
- 1+ year building production AI/ML applications or agents with LLM frameworks such as LangChain or LangGraph.
- Experience with memory patterns, AI evaluation frameworks, prompt optimization and A/B testing, vector stores, RAG, and knowledge organization.
- Strong Python and/or TypeScript development skills, enterprise customer experience, and the ability to explain technical concepts to diverse audiences.
Culture & Benefits
- Collaborative environment with a strong engineering culture and direct impact on customer success and technical best practices.
- Competitive base salary, variable compensation where relevant, meaningful equity, benefits, and perks.
- Medical, dental, and vision coverage.
- Flexible vacation.
- 401(k) plan and meals on in-office days in the US.
- Locally competitive benefits for team members in the EU, UK, and APAC.
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