Solutions Architect

About the role

You will be the architect who wins the technical deal. Before a contract is signed, you show enterprise customers that their AI agents will work, at their scale and under their rules. You build the demos and proofs of concept, answer the architecture questions, and hand delivery a plan they can execute. This is a hands-on engineering role in front of customers. You write code most weeks and spend the rest with CIOs, platform teams and risk officers. You report to the Co-Founder and CTO. Full-time, W-2.

What you will 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, using the customer's own scenarios where you can.

• Prove: scope and deliver 2 to 6 week proofs of concept. Write the code, wire up integrations and 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 proof of concept into a delivery plan our forward-deployed engineers can run from day one.

• Feed back: bring field patterns to product and build reusable demo assets, templates and starter agents.

What we are looking for

• 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 agent framework.

• Strong Python, plus working knowledge of APIs, containers and one major cloud.

• Comfort in regulated environments, where governance, auditability and access control decide the deal.

• Consulting experience: client-facing work, scoping engagements and running workshops with enterprise stakeholders.

• Understanding of tool calling and MCP, guardrails and policy controls, access management, observability and audit trails.

Nice to have

• Experience selling to, or working inside, financial services.

• Kubernetes, observability or AIOps tooling.

• AWS, Azure or GCP certifications.

• A public demo, repo, talk or post about something you built with agents.

Location: Alpharetta, GA (Atlanta office), hybrid 3 days on-site, about 25% travel to customer sites, mostly East Coast.

About Moring

Moring helps enterprises put AI agents into production safely.