Solutions Architect
Summary
Solutions architect at Moring.ai (Alpharetta, GA, hybrid) who wins enterprise AI-agent deals by running technical discovery, building demos and 2-6 week proofs of concept, producing cloud reference architectures, and answering security/model-risk questions. Hands-on Python and LLM-agent framework work, client-facing with CIOs at banks, insurers and asset managers.
The role
Location: Alpharetta, GA (Atlanta office), hybrid 3 days on-site
Type: Full-time, W-2
Reports to: Co-Founder & CTO
You'll be the architect who wins the technical deal. Before a contract is signed, you show enterprise customers that their AI agents will actually work, at their scale and under their rules. You build the demos and proofs of concept, and you answer the architecture questions. Then you hand delivery a plan they can execute.
This is a hands-on engineering role that sits in front of customers. You'll write code most weeks and spend the rest with CIOs, platform teams and risk officers.
About Moring.ai
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.
What you'll do
- 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
What you bring
- 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
Nice to have
- 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.
Benefits
- 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
How we hire
The process takes about two weeks, and every candidate gets the same steps.
- Intro call, 30 min: what you're looking for, and one project you're proud of
- Technical deep dive, 60 min: walk us through an LLM or agent system you built, including the trade-offs
- Demo exercise, 60 min: we send a short customer brief 3 days ahead. You present a demo or architecture, then handle a security objection
- Team conversation, 45 min: meet our Atlanta delivery engineers
- Founder conversation, 30 min: values, equity, and your first 90 days
Moring.ai is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status or any other protected characteristic.