Solution Architect

About the Role

We're looking for a Solution 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.

What You'll Do:

• 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

What You'll Bring

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 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

Agent Engineering & Development:

• 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:

• 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