LangChain
Solutions Architect (Dallas)
Remote Customer Engineering role with clear candidate location fit.
PostedApr 14, 2026
Eligible countries38 accepted countries
Seniority signalLead
Work settingRemote
Accepted candidate locations
Role overview
Solutions Architect (Dallas)
Requirements and responsibilities
Readable role content extracted into sections for faster review.
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
Required Experience
- 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
Required Experience
- 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)
- Experience designing and implementing evaluation frameworks for AI applications
- Strong prompt engineering skills with experience in optimization and A/B testing
- Experience with vector stores, RAG patterns, and knowledge organization
- Experience with tool integration, API design, and error handling patterns
- Strong Python and/or TypeScript development skills
Required Experience
- Customer-facing experience with enterprise customers
- Experience conducting technical assessments or infrastructure audits
- Strong communication skills with ability to explain technical concepts to diverse audiences
Key Attributes
- Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions
- Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences
- Experience working cross-functionally with engineering teams, product teams, and customers
- Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation
- Ability to balance infrastructure architecture with agent development work
- Strong engineering background with hands-on development experience
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