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LangChain

Deployed Architect, Professional Services (San Francisco)

San Francisco, CAOnsite · United States
Staff · FullTime · Customer Engineering
POSTED 9 OCTVERIFIED 23M AGO
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Role
36 days opentrue age
Past the 35d median close
Posted 9 Oct · n=17
Pay
$191k–$219kno pay posted
$168k$284k
Market p25–p75
$205k–$284k
LangChain p25–p75
$191k–$219kn=4
H-1B median · Software engineering
$168k
SF Bay Area · n=1184 · 365d to 15 Nov
CompanyLangChain →
103open roles
Opened · 30d
+12
Closed · 30d
−5
Signal
● Steady+7 net
14d of snapshots · 30d window
Market
9,372open · Staff Software engineering
Opened · 7d
+7828% of open
All software engineering
75,295open
All tracked boards · live 15 Nov · n=9,372
Visa
12H-1B LCAs · FY26
Median wage
$170k
LCAs FY26 · n=12 · to 2026-05-18
AWSGCPAzureKubernetesTerraformLLMs

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)

Source · LangChainFirst seen 2 Nov1 editsOriginal ↗