Tata Consultancy Services

Tata Consultancy Services

Solution Director of Data & AI

New York, NY · Director

Sponsorship not specified$200k-$250kDetected 99 days ago
LLMsSalesBusiness DevelopmentResearchLeadershipPublic Speaking

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odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Third-party placement is common here

32% of this employer's visa filings place the worker at a client company rather than at the employer itself, across 424 clients. Your visa, salary band and layoff exposure would follow the employer of record, not the client.Most common: CITIBANK N.A · BANK OF AMERICA · HUMANA INCFiles as an H-1B dependent employer.

Reported a layoff in this occupation

In a green-card filing decided 2026-03-12, this employer stated it had laid off workers in Software Quality Assurance Analysts and Testers (NY) during the preceding six months. 2 such filings on record.Describes the period before that filing, not necessarily today. Unlike WARN notices this is occupation-specific and federal.

Files H-1B transfers

135 transfer filings in the last year, covering 135 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • This position is part of TCS Industrial Autonomy and Engineering horizontal business unit to drive the growth of Engineering and IoT services for AI and Data in North America. The ideal candidate will have over 13 years of industry experience shaping proposals, building strong client relationships, and drive solution-based sales while collaborating with
  • cross-functional teams to create business opportunities and enhance value for Customers. Experience to sell cloud, data and niche expertise like AI is important to make an impact.

Responsibilities

  • Build strong client relationships by understanding client needs and jointly identifying their challenges and preferences
  • Develop and implement comprehensive business development strategies to drive growth and expand market share for IAE units AI and Data business in the NA.
  • Carry out market analysis and lead business planning and strategic sales activities
  • Drive growth by identifying new opportunities, building client relationships, and closing strategic deals.
  • Collaborate with cross-functional teams to deliver tailored solutions for clients.
  • Actively drive awareness of AI and data solutions with targeted clients - tradeshows, research-led thought leadership, client roadshows and workshops, etc.

Requirements

  • Bachelor's in Engineering/ Master's in Engineering with 13+ years of experience with at least 5+ years of Digital (Cloud, Data and AI ) solution development / sales experience
  • Experience and domain knowledge in Engineering Industries.
  • Working knowledge of AI, data, and cloud with basic knowledge of latest Gen AI skills.

Nice to have

  • Bachelor's or Master's degree in engineering

Skills

  • Digital: Artificial Intelligence(AI)
  • Experience to sell cloud, data and niche expertise like AI is important to make an impact.

Compensation

  • $200,000 - $250,000 a year

Company info

  • Present, promote, and sell AI and Data solutions & services to existing and prospective customers in the North America.
  • Lead the technical discussions with customers for TCS's solutions
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This listing is sourced directly from Tata Consultancy Services's careers page and normalized into a canonical job model.