Field-Embedded Enterprise AI Engineer

Moring AI; Atlanta (GA); On-site; USD 180,000 - 230,000; Full time

Job summary

Moring AI is hiring a Senior AI Engineer to design, build, and deploy AI capabilities into customer environments. You will own end-to-end systems spanning product features and platform primitives, including model access, orchestration, retrieval, and evaluation, with a strong focus on reliability, latency, and security.

You will collaborate with enterprise customers on-site, translating field learnings into product improvements, and mentor a small team while guiding architecture decisions.

Qualifications

• 8–12 years of software engineering experience including cloud-native systems.
• Deep AWS expertise: EKS/ECS, Lambda, IAM, networking, and infrastructure-as-code.
• Strong Python and production engineering habits: testing, observability, code reviews.
• Solid grounding in distributed systems, API design, and event-driven architecture.
• Recent, demonstrable AI depth with hands-on agents, RAG pipelines, or LLM apps.
• Experience with at least one agent framework (LangGraph, CrewAI) and major model APIs.
• Familiarity with MCP, security considerations, and enterprise integration patterns.

Responsibilities

• Design, build, and ship agents, agentic workflows, and LLM-powered features end to end.
• Build retrieval with chunking, embedding strategies, vector search, hybrid search, and evaluation.
• Integrate models and tools via APIs (Anthropic, OpenAI, Bedrock) with security considerations.
• Embed with client teams, map workflows, and deploy AI solutions in customer environments.
• Own AWS infrastructure for AI workloads and operate production services with SLOs.

Skills

Python programming

Cloud-native systems

Distributed systems

API design

SLOs/production engineering

Observability

Tools

AWS (EKS/ECS)

Lambda

Terraform/CDK

LangGraph

CrewAI

OpenAI/Anthropic/Bedrock

Job description

Moring AI is hiring a Senior AI Engineer to design, build, and deploy AI capabilities into customer environments. You will own end-to-end systems spanning product features and platform primitives, including model access, orchestration, retrieval, and evaluation, with a strong focus on reliability, latency, and security.

You will collaborate with enterprise customers on-site, translating field learnings into product improvements, and mentor a small team while guiding architecture decisions.