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Enterprise Architect – AI, Data & Platform Architecture

Techfi Systems

 

Wayne, New Jersey, USA

Posted On: 14 days ago
Experience: 10+ years
Availability: Remote
Openings: 1
Category: Enterprise Architect
Tenure: No Preference/Any
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Description

You will define and guide enterprise-wide architecture across AI/ML, data platforms, cloud infrastructure, and large-scale distributed systems. This role blends enterprise architecture leadership with deep engineering fluency to shape target-state architectures and influence platform strategy.

This role is remote.

Responsibilities

  • Define and govern enterprise architecture strategy for AI, data, and platform ecosystems aligned with business objectives.
  • Own target-state and multi-year architecture roadmaps across data platforms, AI/ML systems, and cloud-native services.
  • Lead architecture for enterprise-scale distributed systems, including event-driven platforms, microservices, and real-time data pipelines.
  • Guide adoption of AI/ML and Generative AI solutions, including LLMs, agents, RAG architectures, and ML pipelines.
  • Embed security, identity, governance, and compliance into platform designs, including IAM, RBAC, and multi-tenant security.

Required Skills

  • 10+ years of experience in enterprise architecture, platform architecture, or solution architecture.
  • Proven experience designing enterprise-scale data platforms, AI/ML systems, and distributed architectures.
  • Strong understanding of modern data architectures, including streaming, event-driven, lakehouse, APIs, and ETL/ELT.
  • Hands-on exposure to AI/ML and Generative AI, including LLMs, agents, RAG, and ML pipelines.
  • Cloud architecture experience on AWS, GCP, or Azure.
  • Experience with security, identity, governance, and compliance architecture in enterprise environments.
  • Strong communication skills with the ability to influence senior leadership and cross-functional teams.

Preferred Skills

  • Experience in large, multi-domain enterprise environments such as FinTech, payments, SaaS, or regulated industries.
  • Practical experience deploying AI-driven platforms in production at scale.
  • Familiarity with event-driven architectures, microservices, and cloud-native platforms.

Education

Any Graduate

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