LangChain
Solutions Architect (NYC)
New York, NY
Sponsorship not specified$170k-$190kDetected 99 days ago
TypeScriptPythonVector DatabasesAWSGCPAzureCloud PlatformsKubernetesTerraformHelmCI/CDPrometheusGrafanaDatadogPlatform EngineeringAPI DevelopmentMachine LearningLLMsRAGAgentic AILangGraphA/B TestingHRISCustomer Success
About the role
- We're looking for a Solutions Architect to join our Professional Services team.
- This role combines software development, infrastructure/platform engineering, and customer-facing skills.
- This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology.
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
- Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments
- 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
Requirements
- 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
- 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure)
- 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
Compensation
- We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
- Actual compensation and offerings will vary based on role, level, and location.
Benefits
- Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
- Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
Company info
- At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.
- With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we're at a stage where we're continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.
- Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.
- At LangChain, our mission is to make intelligent agents ubiquitous.
- We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on.
- We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.
- With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we're at a stage where we're continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together.
- LangChain is a place where your contributions can shape how this technology shows up in the real world.
- Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement.
- We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.
- 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
- Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams
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This listing is sourced directly from LangChain's careers page and normalized into a canonical job model.