Solutions Architect

• Discover: run technical discovery with CIOs, platform-engineering and risk teams at banks, insurers and asset managers. Map their systems, data and controls to the agent use cases that matter
• Demo: build tailored demos of agent workflows and the AI Control Plane, using the customer’s own scenarios where you can
• Prove: scope and deliver 2-6 week proofs of concept. Write the code, wire up integrations, measure results against agreed success criteria
• Design: produce reference architectures for agent deployment on AWS, Azure or GCP, covering identity, data access, observability and guardrails
• De-risk: answer security, compliance and model-risk questionnaires (SOC 2, data residency, audit logging, human-in-the-loop controls)
• Hand off: turn every won POC into a delivery plan our forward-deployed engineers can run with from day one
• Feed back: bring field patterns to product, and build reusable demo assets, templates and starter agents for the team

Product Demonstration, Artificial Intelligence (AI) Agents, Proof of Concept, Computer Programming, Risk, Artificial Intelligence (AI), Fortune 500 Customers, Asset Management, Financial Services, Use Cases, * 8+ years in software engineering, solutions engineering, solutions architecture or forward-deployed engineering for enterprise customers

• Hands-on experience building LLM applications or agents: prompt and tool design, RAG, evaluation, and at least one framework such as LangGraph, CrewAI, Semantic Kernel or the OpenAI or Anthropic agent SDKs
• Strong Python, plus working knowledge of APIs, containers and one major cloud
• You can explain an architecture to an engineer and its business case to a CIO in the same meeting
• Comfort in regulated environments, where governance, auditability and access control decide the deal
• Consulting experience: client-facing work at a consulting firm or systems integrator, scoping engagements, running workshops and owning outcomes with enterprise stakeholders
• Solid understanding of agentic tools, AI governance and agent deployment: tool calling and MCP, guardrails and policy controls, access management, observability and audit trails, and taking agents from pilot to production at enterprise scale, * Experience selling to, or working inside, financial services
• Kubernetes, observability or AIOps tooling
• Cloud or AI certifications (AWS, Azure, GCP)
• A public demo, repo, talk or post about something you built with agents

We don’t expect you to match every line. If you’ve built with LLMs and enjoy putting that work in front of customers, we’d like to hear from you.

• Early-employee equity
• Employer-paid health insurance
• Hybrid schedule from our Alpharetta office, about 25% travel to customer sites, mostly East Coast
• Budget for certifications, conferences and AI tooling

Moring.ai helps enterprises put AI agents into production safely. Our forward-deployed engineers build agents alongside customer teams, and our AI Control Plane governs them once they’re live. A Fortune 500 asset manager runs on Moring today, and we’re profitable quarter over quarter. Our Atlanta team builds and delivers for our largest financial-services customers. You’ll join it as our first dedicated solutions architect.