Solutions Architect

About Us:

At Lang Chain, 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.

Today,
Lang Chain, Lang Graph, Lang Smith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust Lang Chain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500
.

With $125M raised at Series B from IVP, Sequoia, Benchmark, Capital

G, 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. Lang Chain is a place where your contributions can shape how this technology shows up in the real world.

We're looking for a Solutions 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.

• 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

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 Git Ops 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 (Lang Chain, Lang Graph, 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…