AI Architect

State / Region / Province

Arizona, Connecticut, Indiana, North Carolina, Ohio, Texas

Country

USA

Domain

Delivery

Interest Group

Company

ITL USA

Requisition

148821

Technical Skills 1

Technical Skills 2

The Infosys Retail, Consumer Goods, and Logistics unit stands as a globally respected partner of choice, dedicated to helping clients achieve their business goals through cutting-edge technology and seamless services. Our unit offers a dynamic forum where projects and teams can effectively learn, adopt, and excel in all technologies. We foster a vibrant community that leverages shared skills and experiences to deliver high-quality, value-enhanced solutions.

Join us and become part of a team that drives innovation, operational efficiency, and sustainable growth in the retail, consumer goods, and logistics sector. Together, we can shape the future of these industries and achieve remarkable success.

• 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.

• A strong focus on innovation and scalable analytics solutions.
• 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.

• Architect and implement production‑grade AI agent solutions on Google Cloud Platform (GCP), with Azure as a supporting cloud environment where required.
• Design end‑to‑end AI systems including:
  • Agent orchestration
  • Short‑term memory
  • Long‑term memory
  • Context management
  • Tool integrations
  • Workflow execution
  • Evaluation pipelines
• Build and standardize architecture for production‑ready AI agents, ensuring scalability, resilience, security, and…