About the job
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.
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
Qualifications
Minimum
- 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer
- 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
- 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
- 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
Preferred
No preferred qualifications listed.