Senior AI Engineer – Data & Engineering

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python SQL Flask Analytics Data Extraction AWS

Job Description

Senior AI Engineer – Data & Engineering (Content & Data Management)


Role Overview

We are looking for a Senior AI Engineer – Data & Engineering to design and build AI-enabled data and content platforms that automate ingestion, enrichment, governance, and analytics across the enterprise data lifecycle.

This role focuses on embedding intelligence directly into systems so that data becomes trusted, explainable, governed, and scalable by design rather than through manual intervention.

You will contribute to building AI-first platforms, supporting document intelligence, predictive governance, metadata automation, analytics copilots, and autonomous pipeline reliability.

This is a platform engineering role — not a reporting or dashboard-only role.


Key Responsibilities

AI-Enabled Data Platform Engineering

  • Build and maintain AI-enabled pipelines across ingestion, transformation, governance, and analytics layers
  • Support metadata-driven architectures and enterprise data catalogs
  • Implement intelligent validation and enrichment mechanisms across workflows

Data Quality & Integrity Automation

  • Monitor pipelines for schema drift, anomalies, and integrity issues
  • Develop automated quality checks and AI-assisted remediation workflows
  • Improve reliability through proactive data controls

Analytics & AI Insights Enablement

  • Deploy predictive analytics models and operational dashboards
  • Support NLP workflows for classification, summarization, and metadata extraction
  • Deliver near real-time analytics capabilities for business decision-making

Workflow Automation & AI Copilots

  • Replace manual validation/reporting with AI-assisted automation
  • Support AI-driven alerting and guided analytics experiences
  • Enable business users to leverage AI copilots effectively

Platform & Product Engineering Mindset

  • Build reusable analytics components, APIs, and templates
  • Treat analytics capabilities as scalable platform assets
  • Improve usability and adoption across enterprise data consumers

Collaboration & Stakeholder Engagement

  • Translate business problems into scalable AI-enabled data solutions
  • Work with cross-functional engineering and analytics teams globally
  • Document workflows and platform capabilities clearly


Required Experience & Qualifications

  • 5+ years experience in Data Engineering, AI Platforms, Analytics, or Large-Scale Content Systems
  • 3+ years designing or operating AI-enabled platforms on AWS or GCP
  • Strong Python expertise (FastAPI / Flask preferred)
  • Advanced SQL skills supporting both analytical and low-latency workloads
  • Experience managing end-to-end data and content lifecycles
  • Hands-on implementation of automation-first or AI-assisted workflows
  • Experience working in enterprise-scale distributed environments
  • Experience supporting multiple domains/products in matrix organizations
  • Strong stakeholder collaboration experience
  • Production system ownership including monitoring, incident response, and performance tuning


Preferred Experience

  • Exposure to regulated industries (Financial Services, Healthcare, Telecom, Energy, Consulting)
  • Experience with document intelligence / unstructured data analytics
  • Experience embedding analytics into platform or client-facing products


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