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AI Architect

Infosys Consulting - Location not specified

Posted Jun 12, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Verification
Not verified checked Jun 7, 2026
Salary
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401(k) match
Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Staff Plus From the posting source checked Jun 20, 2026

Schedule

Shift type
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Weekend work
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Application

Cover letter
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Assessment
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Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

AI Architect In the assigned Job Role of Data Science Consultant 3, your Area Of Responsibility will be as below: • Review data preparation tasks, and plans to address patterns or anomalies, while ensuring data readiness for advanced modeling and AI. • Review models for complex use cases (e.g., forecasting models, LLM-based solutions), and refine algorithms to meet business needs. • Review plan for smooth deployment into scalable, production-ready solutions. • Review test plans and test results for analytics use cases, while defining optimization standards for model accuracy and stability, in alignment with business goals. • Build models and analytics solutions tailored to business needs. • Ensure quality and scalability across client engagements while actively contributing to knowledge assets and innovation streams. • Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions. • Review and refine analytics problems; identify data sources and extract from diverse environments. • Oversee analysis execution and drive business insights. • Create monitoring strategies across multiple projects, embedding governance frameworks to ensure robustness, reliability, and risk awareness. • Review monitoring frameworks, refine documentation/reporting templates, and present insights on anomalies or slippages to stakeholders. • Refine documentation strategy across teams, ensuring transparency and reproducibility of complex analytics solutions. • Collaborate with cross-functional teams, ensuring alignment between analytics delivery and business strategy. • Review analytics outputs for adherence to quality frameworks and project commitments. • Recommend improvements to quality metrics

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