Lead AI Deployment Engineer — Enterprise Solutions

United States Digital Space LLC

United States

Remote

USD 162,000 - 191,000

Full time

8 days ago

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Benefits offered by this job

RSUs
Parental leave
Unlimited PTO
Hybrid work model
Learning platform
Well-being programs

Job summary

the company seeks a Lead Deployment Engineer to guide AI-augmented delivery for enterprise customers. You will direct AI agents to build data models, KPIs, dashboards, and operational solutions, translating client needs into precise specifications and ensuring business relevance.

You will collaborate with IT and business stakeholders, manage scope and timelines, and drive measurable value while maintaining high standards of data quality and client satisfaction.

Qualifications

  • Bachelor’s or Master’s in Technology Management, Business Informatics, Computer Science, Engineering, or related field.
  • Fluency in English required; travel up to 50% may be necessary.
  • Experience in management or IT/solution consulting within software vendors, consulting firms, or SI environments.

Responsibilities

  • Lead customer workshops and translate business needs into technical solutions.
  • Direct AI-assisted delivery tools to build data models, KPIs, and dashboards.
  • Define project scope, data requirements, and success criteria with stakeholders.
  • Ensure data connectivity, data quality, and measurable business impact.

Skills

Management consulting
IT consulting
AI fluency
Business domain expertise
Consulting skills
Analytical mindset
Learning agility
English fluency

Education

Bachelor’s or Master’s in Technology Management / CS / Eng / Business

Tools

PQL
SQL
Python

Job description

the company seeks a Lead Deployment Engineer to guide AI-augmented delivery for enterprise customers. You will direct AI agents to build data models, KPIs, dashboards, and operational solutions, translating client needs into precise specifications and ensuring business relevance.

You will collaborate with IT and business stakeholders, manage scope and timelines, and drive measurable value while maintaining high standards of data quality and client satisfaction.

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