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AI Engineer Jobs

Senior AI Platform Engineer (Tech Lead)

Moring Ai

Location
Onsite (Alpharetta, Georgia)
Compensation
$100k - $125k/yr
Employment
Full-time
Level
Senior Level
Posted 6 days ago

About the role

Moring builds production-grade enterprise AI for regulated industries like financial services. This role leads a small engineering team to design, build, and deploy agentic AI workflows and platform services directly within customer cloud environments.

Skills

Python Kubernetes AWS FastAPI AI Engineering LLM RAG Agentic AI API Design Distributed Systems Terraform CI/CD Observability Software Architecture Technical Leadership MCP

Perks

  • Stock Options

Full job details

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)