Principal AI Engineer — Enterprise Agentic Systems (Hybrid)

NAM Info Inc; New York (NY); Hybrid; USD 210,000 - 320,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

NAM Info Inc. in NYC is hiring a Staff/Principal AI Engineer to lead enterprise-scale agentic AI implementations for Fortune 500 clients. This hands-on role designs autonomous tool‑calling AI systems that reason over enterprise data and operate at scale with strict latency, cost, and governance needs.

You will own data pipelines, backend services, orchestration, evaluation harness, and cloud infra end‑to‑end, guiding production deployments and mentoring other engineers.

Qualifications

• 15+ years of software engineering experience with hands-on large-scale Python.
• Strong systems language experience (Go, Rust, Java, or C/C++).
• Solid data structures and algorithms; APIs and microservices expertise.
• Hands-on data pipelines and production‑grade distributed systems.
• 2+ years of hands‑on LLM engineering and agentic systems production.

Responsibilities

• Lead end‑to‑end agentic AI systems from data pipelines to cloud infrastructure.
• Design and ship tool‑calling agents with secure, scalable interfaces.
• Own evaluation harness, governance, and reliability patterns.
• Collaborate with Fortune 500 clients and cross‑functional teams.
• Mentor engineers and raise engineering standards across the team.

Skills

Python

Go

Rust

Java

C/C++

APIs & microservices

Distributed systems

Data pipelines

LLM engineering

Tool calling

Tools

LangGraph

Google ADK

CrewAI

Claude Agent SDK

Milvus

Pinecone

Weaviate

FAISS

LangSmith

Langfuse

Terraform

ECS/EKS

S3

DynamoDB

Redshift

Job description

NAM Info Inc. in NYC is hiring a Staff/Principal AI Engineer to lead enterprise-scale agentic AI implementations for Fortune 500 clients. This hands-on role designs autonomous tool‑calling AI systems that reason over enterprise data and operate at scale with strict latency, cost, and governance needs.

You will own data pipelines, backend services, orchestration, evaluation harness, and cloud infra end‑to‑end, guiding production deployments and mentoring other engineers.