Solutions Architect

About the role

This Solutions Architect role sits within the Professional Services organization at LangChain. You will own the design, deployment, and optimization of production-grade AI infrastructure and agentic systems for enterprise customers. The position requires you to architect scalable, secure, and highly available infrastructures that power real-world agent applications. You will blend software development, platform engineering, and direct client interaction to solve complex technical challenges. A core part of the role involves conducting technical assessments and shaping best practices for current and future AI technology stacks. You will work closely with cross-functional teams to ensure delivered solutions meet strict reliability and performance standards. The position provides direct influence over customer success and long-term platform strategy.

Key facts

What you'll do

• Lead technical discovery sessions with enterprise clients to translate business requirements into robust AI infrastructure roadmaps.
• Design and implement scalable Kubernetes cluster architectures on GCP, AWS, and Azure for LangChain platform deployments.
• Architect multi-agent system frameworks using LangChain, LangGraph, and related open-source tools to meet specific enterprise objectives.
• Develop comprehensive evaluation strategies and A/B testing methodologies for measuring agent performance and business impact.
• Define and manage Infrastructure as Code pipelines using Terraform and Helm within GitOps workflows to ensure repeatable deployments.
• Partner with Product and Engineering teams to iterate on platform components and improve developer experience for agent building.
• Establish high-availability, disaster recovery, and multi-region strategies that minimize downtime for critical agent workloads.
• Implement robust networking, security, and secrets management controls including SSO, RBAC, and TLS for production environments.
• Create detailed technical designs and documentation for database selection, sizing, and high availability configurations.
• Guide customers through maturity assessments and infrastructure audits to identify optimization and risk mitigation opportunities.

Requirements

• Bring 7 or more years of hands-on, technical, customer-facing experience, such as Solutions Architect or Forward Deployed Engineer roles.
• Demonstrate background as a founder with the necessary skillsets if transitioning from a founding role into this position.
• Accumulate over 3+ years of experience designing and deploying production infrastructure on major cloud platforms like GCP, AWS, or Azure.
• Show strong expertise with Kubernetes cluster design, autoscaling configurations, and multi-zone deployments across GKE, EKS, and AKS.
• Apply Infrastructure as Code tools including Terraform and Helm while adhering to GitOps practices in operational settings.
• Maintain deep knowledge of database systems, covering relational databases and in-memory data stores for high availability and scaling.
• Design and manage high-availability and disaster recovery solutions that ensure business continuity for agent platforms.
• Exhibit firm understanding of networking and security fundamentals such as SSO, RBAC, TLS, and secrets management implementations.
• Utilize observability tools like Prometheus, Grafana, and Datadog for monitoring and troubleshooting production workloads.
• Build and manage CI/CD pipelines that support both infrastructure provisioning and application lifecycle management.
• Accumulate 1+ years of experience building production AI or ML applications and agent-based systems in live environments.
• Show strong familiarity with LLM frameworks, specifically LangChain, LangGraph, or comparable agent-building libraries.
• Apply state management patterns effectively, handling both short-term and long-term memory architectures.
• Design and deploy evaluation frameworks that quantify agent performance and validate business outcomes.
• Execute advanced prompt engineering techniques, including optimization strategies and structured A/B testing.
• Implement vector stores, RAG patterns, and sophisticated knowledge organization strategies for enterprise contexts.
• Integrate tools, design APIs, and handle error management patterns within agent workflows.
• Demonstrate advanced development capabilities in Python and/or TypeScript for building maintainable solutions.
• Engage with enterprise customers through technical consultations and detailed requirement gathering sessions.
• Conduct infrastructure audits and technical assessments that inform strategic client decisions.
• Communicate intricate technical concepts clearly to both technical and non-technical stakeholders.

Practical notes

The role is based in Austin, TX, and requires full-time engagement. There are no specific travel requirements, visa sponsorships, or application deadlines mentioned in the current job description. Candidates should be prepared for direct collaboration with engineering and product teams in a fast-paced, production-focused environment.