Deployed Architect, Professional Services (San Francisco)
- Market p25–p75
- $205k–$284k
- LangChain p25–p75
- $191k–$219kn=4
- H-1B median · Software engineering
- $168k
- Opened · 30d
- +12
- Closed · 30d
- −5
- Signal
- ● Steady+7 net
- Opened · 7d
- +7828% of open
- All software engineering
- 75,295open
About Us
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
About the Role
We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems.
This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains.
This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture.
Key Responsibilities
Infrastructure & Platform Engineering: 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
Agent Engineering & Development: 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
Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams
What We're Looking For
Required Experience
7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply
Infrastructure & Platform
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
Agent Engineering & Development
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)