Senior AI Platform Engineer (Tech Lead).

About Us

Moring.ai builds enterprise AI that runs in production for regulated industries: financial services and other compliance-heavy organizations. We ship AI applications and agents inside our customers' own cloud environments, wired into the systems they already run. Not slideware, not demos.

We're early-stage, lean, and profitable, so what you ship reaches serious enterprises fast.

The Role

We are building an AI platform for a large financial services enterprise. It lets developers inside that organization build and deploy agentic AI workflows: Python applications that call LLMs, use tools, and run as agents on Kubernetes. The platform includes an LLM gateway, an agent runtime, MCP servers, a skills registry, retrieval, evals, observability, and governance.

We are hiring a Tech Lead to lead the engineers building it. You have 7–9 years of software engineering experience and you are very strong on the software side: you write clean, well-tested Python, you design APIs and backend systems well, and you can go full stack when needed. You have a good working understanding of AI (agents, RAG, LLM applications) and you have built some of it hands-on, but the thing we are hiring you for is engineering: the hard problems in AI right now are reliability, cost, latency, security, and testing systems that don't give the same answer twice.

This is a hands-on lead role. You will write a large share of the code, review the rest, break the work down for the team, and keep the platform shippable. The architect sets the overall design; you make it real.

What You'll Do

• Lead a team of 3–5 engineers: break down the work, set priorities with the architect and the CEO, review code, and keep delivery on track.
• Write production code across the platform: the LLM gateway, the agent runtime, MCP servers, the skills and asset registry, evals, and the APIs developers use to deploy agents.
• Design and build the APIs and services the platform exposes, in Python, with the habits of a production engineer: tests, observability, clean interfaces, clear error handling.
• Build the developer-facing parts of the platform (CLI, SDK, or web UI) so an engineer at the customer can go from an idea to a deployed agent without asking us.
• Own code quality: set the coding standards, the review process, the test strategy, and the CI/CD pipeline, and hold the team to them.
• Build and extend the evaluation harness so AI changes ship with evidence.
• Deploy into the customer's environment: their AWS accounts, EKS clusters, private networks, and internal registries. Reproducible, with no manual steps.
• Work with the customer's engineers in design sessions, demos, and security reviews.
• Operate what the team builds: production ownership, on-call rotation, performance and cost tuning.
• Mentor the engineers on the team and raise their engineering and AI practices.

What We're Looking For

• 7–9 years of software engineering experience shipping production systems: backend, platform, or full stack.
• Expert Python. You have built APIs and services in Python (FastAPI or comparable), you know its testing and packaging ecosystem, and you can write code others want to copy.
• Very strong software fundamentals: data structures, API design, distributed systems, databases, concurrency, and security basics.
• Full-stack ability preferred (React or comparable front end), but at minimum you can design and build APIs and backend systems end to end.
• Good working knowledge of AWS (EKS or ECS, Lambda, IAM, networking) and Kubernetes, and some infrastructure-as-code (Terraform or CDK).
• Good understanding of AI engineering: you have built agents, RAG pipelines, or LLM applications hands-on, you know the major model APIs (Anthropic, OpenAI, Bedrock) and at least one agent framework, and you understand context management, token economics, and how to test non-deterministic systems.
• Familiarity with MCP.
• You have led a small team before, or you have been the engineer everyone else goes to and you are ready to lead.
• Experience inside large enterprises is a plus, regulated ones (financial services, insurance, healthcare) more so.
• You can explain a technical trade-off in plain language to someone who isn't an engineer.

Role Details

• Location: Alpharetta, GA (on-site)
• Years of experience: 7–9
• Type: Full-time, hands-on tech lead
• Salary: 100-125K+Stock Options
• Travel: Up to 10% to customer sites
• Work authorization: Must be authorized to work in the United States (GC/EAD/US Citizen)