Solutions Architect

Responsibilities

Infrastructure & Platform Engineering

• Design scalable, highly available infrastructure for AI platform deployments, including compute, storage, networking, and security.
• Develop enterprise integration patterns, Infrastructure as Code using Terraform and Helm, multi-region high-availability and disaster-recovery strategies, and CI/CD pipelines.

Agent Engineering & Development

• Design multi-agent systems using different patterns.
• Implement agent logic using modern frameworks such as LangChain and LangGraph.
• Design comprehensive evaluation frameworks.
• Optimize prompts through A/B testing.
• Guide deployment and operations.

Customer Engagement & Assessment

• Lead technical maturity assessments.
• Work directly with enterprise customers to understand requirements and present recommendations.
• Partner with Engagement Managers and Product and Engineering teams.

Requirements

Experience

• 7+ years of experience in 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 such as GCP, AWS, or Azure.
• 1+ years of experience building production AI/ML applications or agents.
• Customer-facing experience with enterprise customers.
• Experience conducting technical assessments or infrastructure audits.

Infrastructure & Platform

• Strong Kubernetes experience, including cluster design, autoscaling, and multi-zone deployments.
• Experience with Infrastructure as Code using Terraform and Helm, as well as GitOps practices.
• Knowledge of relational databases and in-memory data stores, including high availability, replication, backup strategies, and sizing.
• Experience designing high-availability and disaster-recovery solutions.
• Strong understanding of networking, security—including SSO/RBAC, TLS, and secrets management—and observability.
• Experience with CI/CD pipelines for infrastructure and applications.

Agent Engineering

• Strong experience with LLM frameworks such as LangChain, LangGraph, or similar frameworks for building agent-based applications.
• Experience with state-management patterns, including short-term and long-term memory.
• Experience designing and implementing evaluation frameworks for AI applications.
• Strong prompt-engineering skills, including optimization and A/B testing.
• Experience with vector stores, retrieval-augmented generation (RAG) patterns, and knowledge organization.
• Experience with tool integration, API design, and error-handling patterns.
• Strong Python and/or TypeScript development skills.

Customer-Facing and Collaboration

• Strong communication skills and the ability to explain technical concepts to diverse audiences.
• Strong problem-solving skills and the ability to analyze complex requirements and design elegant solutions.
• Experience working cross-functionally with engineering teams, product teams, and customers.
• A consultative approach with the 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.

Compensation & Benefits

• Compensation is based on experience and location.
• The role includes base salary, variable compensation where relevant, meaningful equity, benefits, and perks; actual offerings vary by role, level, and location.
• Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
• Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and meals on in-office days in the US.

Work Arrangement

• Remote, based in London, UK, with up to 25% travel.