Solutions Architect

🕒 April 16

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LangChain

11 - 50 employees

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

💰 $25M Series A on 2024-02

Artificial Intelligence • B2B • SaaS

LangChain is a composable framework designed to assist developers throughout the entire lifecycle of Large Language Model (LLM) applications. Their suite of products, including LangGraph and LangSmith, offers tools for building, deploying, and managing applications that can reason and operate at scale. With a focus on operational efficiency and improved performance, LangChain supports a wide range of industries through its innovative offerings.

📋 Description

• work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. • architect scalable, secure infrastructure deployments and build reliable, well-evaluated agent applications that solve real business problems. • lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams.

🎯 Requirements

• 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. • 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) • Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments • Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices • Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing • Experience designing high-availability and disaster recovery solutions • Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) • Experience with CI/CD pipelines for infrastructure and applications • 1+ years of experience building production AI/ML applications or agents • Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications • Experience with state management patterns (short-term and long-term memory) • Experience designing and implementing evaluation frameworks for AI applications • Strong prompt engineering skills with experience in optimization and A/B testing • Experience with vector stores, RAG patterns, and knowledge organization • Experience with tool integration, API design, and error handling patterns • Strong Python and/or TypeScript development skills • Customer-facing experience with enterprise customers • Experience conducting technical assessments or infrastructure audits • Strong communication skills with ability to explain technical concepts to diverse audiences

🏖️ Benefits

• medical, dental, and vision coverage • flexible vacation • a 401(k) plan • meals on in-office days in the US and more.

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