Solutions Architect (san Francisco)

LangChain LangChain · Data AI · San Francisco, CA · Customer Engineering

LangChain is seeking a Solutions Architect to join their Professional Services team. The role involves working with enterprise customers to design, deploy, and optimize AI infrastructure and agent systems. Responsibilities include architecting scalable infrastructure, building reliable agent applications, and customer engagement. This position requires a blend of software development, infrastructure engineering, and customer-facing skills, with a focus on multi-agent systems and production-grade AI deployments.

What you'd actually do

  1. Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines
  2. Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations
  3. Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams

Skills

Required

  • 7+ years of experience in a technical, hands-on customer-facing roles
  • 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

Nice to have

  • former founders

What the JD emphasized

  • production-grade AI infrastructure and agent systems
  • scalable, secure infrastructure deployments
  • reliable, well-evaluated agent applications
  • multi-agent system architecture
  • production infrastructure
  • production AI/ML applications or agents
  • production AI products

Other signals

  • design, deploy, and optimize production-grade AI infrastructure and agent systems
  • architecting scalable, secure infrastructure deployments
  • building reliable, well-evaluated agent applications
  • multi-agent system architecture
  • customer success
  • best practices
  • cutting-edge AI technology
  • collaborative team environment
  • strong engineering culture