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AI Architect
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ITL USA
Blue Ash, OH (In Person)
Full-Time
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Job Description
Apply now You have successfully copied the job share URL to clipboard! × Job details Job Role Data Science Consultant 3 Career Role Data Scientist Work Location Blue Ash, OH, Cincinnati, OH, Hartford, CT, Indianapolis, IN, Phoenix, AZ, Raleigh, NC, Richardson, TX State / Region / Province Arizona, Connecticut, Indiana, North Carolina, Ohio, Texas Country USA Domain Delivery Interest Group Infosys Limited Company ITL USA Requisition
ID 148821BR
Technical Skills 1 Technology|AI Hyperscalers|Google Agentic AI Services Technical Skills 2 Technology|AI Hyperscalers|Azure Agentic AI Services Overview 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. 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 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.
Your contribution to the team:
- 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. Required Skill and Experience
- 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: o Agent orchestration o Short-term memory o Long-term memory o Context management o Tool integrations o Workflow execution o Evaluation pipelines
- Build and standardize architecture for production-ready AI agents, ensuring scalability, resilience, security, and maintainability.
- Define and implement AI Gateway patterns for model access, routing, authentication, rate limiting, and policy enforcement.
- Design and deploy guardrails for responsible AI, safety, compliance, prompt protection, hallucination mitigation, and output validation.
- Establish tracing and observability frameworks for AI applications using GCP-native monitoring capabilities and Dynatrace.
- Implement evaluation services for AI systems, including: o Offline evaluation o Online evaluation o Model and agent performance benchmarking o Quality and reliability measurement
- Define and implement architecture for memory systems, including short-term conversational memory and persistent long-term memory.
- Collaborate with engineering, data, product, security, and customer stakeholders to align AI solutions with business and technical requirements.
- Lead technical discussions with different customer stakeholders, translating business needs into scalable AI architectures.
- Drive architecture decisions under aggressive timelines while maintaining delivery quality and engineering rigor.
- Ensure AI systems adhere to enterprise standards for governance, privacy, security, compliance, and operational excellence.
- Provide technical leadership, mentorship, and architecture guidance to cross-functional teams. Preferred Skill and Experience Add details about Key Technical and Domain Skills Additional Required Qualifications
- Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
- This position may require relocation and/or travel to work/project location.
- Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply.