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# Gen AI Solution Engineer

- **Company:** Infosys
- **Location:** Houston, TX, United States
- **Salary:** $103,500.0 - $188,888.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Python (Programming Language), SAS (Software), Large Language Models, Deep Learning, Generative AI, Data Analytics
- **Published:** October 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a04dbda0a7667791

## About the Role

* Proactive problem-solving ability for complex, data-driven business challenges.
 * Deep technical expertise across advanced modeling and AI use cases.
 * A strategic mindset to align analytics with business goals.
 * Ability to mentor team members and drive continuous improvement.
 * Strong communication and knowledge-sharing capabilities.

## Description

* 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 and guide team members to align with standards.
 * Identify and recommend model changes needed for successful deployment.
 * Engage in creation and refinement of IP assets such as analytics prototypes and accelerators.
 * Develop insights, whitepapers, and proof-of-concept summaries that highlight innovative thinking.
 * Review innovative models and applications in non-ML, ML, deep learning, or LLM areas.
 * Support participation in forums and internal knowledge exchanges.
 * Deliver training sessions on technical and analytics-specific topics.
 * Collaborate on content creation and mentor team members through hands- on guidance in live projects.
 * Provide input for segment and unit-level business plans.