Senior AI Platform Architect

Moring Ai•Newark, NJ

22h•$160,000 - $180,000•Onsite

About The Position

Moring.ai is hiring a Senior AI Platform Architect to own the architecture of an AI platform for a large financial services enterprise. The platform enables the customer's developers to build and deploy Python-based agentic AI workflows that call LLMs, use tools, and run as agents on Kubernetes. Its components include an LLM gateway, agent runtime, MCP servers for tools and data, a skills registry, retrieval, evaluation, observability, and identity and governance controls. This is a hands-on architecture role involving design documents, code reviews, reference implementations, and architecture decisions that guide the engineering team. The architect will also present and defend the architecture to customer architects, platform teams, security teams, and model risk reviewers, incorporating their constraints into the design. The role includes mentoring senior engineers and improving platform engineering practices. The position is based 100% onsite in Newark, New Jersey, with travel of up to 10% to customer sites. Applicants must be authorized to work in the United States (GC/EAD/US Citizen).

Requirements

10–12 years of software engineering experience, with substantial experience building cloud, developer, container, or internal platforms, or working as a software architect with deep platform knowledge.
Very strong Kubernetes experience designing and running production workloads, including understanding of networking, scheduling, security, multi-tenancy, and operators.
Very good AWS experience, including EKS, IAM, VPC networking, private endpoints, and Terraform or CDK; prior experience building and operating a cloud platform.
Solid understanding of AI platform concepts, including LLM gateways, agent runtimes such as Bedrock AgentCore or comparable systems, MCP, RAG and retrieval, skills and tool registries, evaluations, and AI observability.
Strong distributed systems, API design, and security fundamentals.
Comfort with Python sufficient to build reference implementations and review code.
Experience working inside large enterprises; experience in regulated industries such as financial services, insurance, or healthcare is preferred.
Ability to write clear design documents and defend trade-offs before a client's chief architect.
Authorization to work in the United States (GC/EAD/US Citizen).

Nice To Haves

Experience working in regulated industries, preferably financial services, insurance, or healthcare.

Responsibilities

Own the end-to-end architecture of the AI platform, including the gateway, agent runtime, MCP layer, skills and asset registry, retrieval, evaluations, observability, identity, and governance.
Design how agents run on Kubernetes, including packaging, scheduling, scaling, isolation, networking, state and memory, versioning, promotion, and rollback.
Design the AWS foundation for a regulated enterprise with restricted egress, including EKS, IAM, networking, private endpoints, and infrastructure as code.
Define the identity model for agents, including agent authentication, acting on behalf of users without exceeding their access, and audit trails.
Define the developer experience for taking an idea to a deployed agent with appropriate guardrails and minimal friction.
Set reusable, versioned, and governed patterns for MCP servers, skills, tools, and prompts.
Write architecture documents and reference implementations, and review team designs and code against them.
Present the architecture to the customer's chief architect, platform teams, security reviewers, and model risk reviewers, and incorporate their constraints.
Evaluate AI platform capabilities, including model providers, agent frameworks, runtimes, and registries, and decide what belongs in the platform.
Mentor senior engineers and raise the team's platform engineering practices.