Lead Enterprise AI Platform Architect

Tiger Analytics Inc.

United States

Remote

USD 150,000 - 210,000

Full time

14 days+
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Job summary

Tiger Analytics is seeking a highly experienced Lead AI Engineer to lead the end-to-end AI engineering workstream for the Luma platform. This is a hands‑on technical leadership role responsible for driving the architecture, design, and delivery of enterprise‑scale Agentic AI solutions while serving as the primary technical interface for the client.

The ideal candidate will combine deep expertise in AI engineering, distributed systems, cloud‑native architectures, and MLOps with exceptional

Qualifications

  • 10–15+ years in software engineering with 5+ years leading AI/ML engineering teams.
  • Experience building and deploying enterprise AI platforms on AWS.
  • Strong client-facing, solution architecture, and cross-functional leadership experience.

Responsibilities

  • Lead AI architecture and engineering roadmap for Agentic AI platforms.
  • Design and deliver scalable, production-grade AI solutions.
  • Oversee AI platform services, backend APIs, microservices, MLOps, observability, and cloud infrastructure.
  • Partner with clients to translate business needs into AI solutions and lead architecture discussions.
  • Mentor AI engineers, conduct design/code reviews, and drive engineering best practices.
  • Lead multiple engineering teams, manage delivery, risks, and technical roadmaps.
  • Evaluate and adopt emerging AI technologies and frameworks.
  • Leadership: Client-facing consulting, architecture design, stakeholder management, mentoring, and technical leadership.

Skills

GenAI
LLMs
Agentic AI
Multi-Agent Systems
RAG
Prompt Engineering
AI Guardrails
MLOps
Python
Golang
REST APIs
Async Programming
AWS
Cloud Architecture
Kubernetes
Distributed Systems

Tools

Docker
Kubernetes
REST APIs
AWS Cloud

Job description

Tiger Analytics is seeking a highly experienced Lead AI Engineer to lead the end-to-end AI engineering workstream for the Luma platform. This is a hands‑on technical leadership role responsible for driving the architecture, design, and delivery of enterprise‑scale Agentic AI solutions while serving as the primary technical interface for the client.

The ideal candidate will combine deep expertise in AI engineering, distributed systems, cloud‑native architectures, and MLOps with exceptional

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