INS/ Principal - AI Architect

Infosys•Houston, NY

22h•Onsite

About The Position

The applicant should have deep, hands-on experience architecting, designing, and implementing enterprise-grade AI, Machine Learning, and Generative AI solutions, and experience leading technical teams delivering complex AI and automation engagements across industries. The role involves translating business problems into AI solution architecture, hands-on experience designing AI/ML platform architectures on cloud-native and hybrid environments, and experience with MLOps/LLMOps practices. Additionally, the role requires strong proficiency in Python and ML/AI frameworks, experience with cloud AI/ML services, data architecture and engineering, integrating AI solutions into enterprise systems, and understanding of AI governance, responsible AI practices, model risk management, and data privacy/security considerations. The role also involves integrating AI/GenAI capabilities with automation platforms and requires travel to client sites as needed. Consulting responsibilities include client relationship management, leading client delivery teams, establishing expertise in a focus area, mentoring and developing consultants, and supporting sales and firm development activities.

Requirements

Deep, hands-on experience architecting, designing, and implementing enterprise-grade AI, Machine Learning, and Generative AI solutions.
Experience leading technical teams delivering complex AI and automation engagements across industries.
Experience architecting and implementing AI/ML solutions across multiple domains, including: Generative AI and Large Language Model (LLM) based solutions, Predictive and prescriptive Machine Learning models, Computer Vision, Natural Language Processing (NLP) and Conversational AI, Intelligent Document Processing (IDP / iOCR), Agentic AI systems and multi-agent orchestration.
Worked across the end-to-end AI solution lifecycle: use case discovery, data assessment, solution architecture, model development, deployment, and monitoring.
Experience translating business problems into AI solution architecture using design thinking and structured problem-solving techniques.
Hands-on experience designing AI/ML platform architectures on cloud-native and hybrid environments (AWS, Azure, GCP).
Hands-on experience with LLM frameworks and patterns (LangChain, LlamaIndex, Semantic Kernel), vector databases, and Retrieval-Augmented Generation (RAG) architectures.
Experience with MLOps/LLMOps practices, including model lifecycle management, CI/CD for ML, monitoring, and retraining pipelines.
Strong hands-on proficiency in Python and ML/AI frameworks such as TensorFlow, PyTorch.
Experience with cloud AI/ML services such as Azure OpenAI, AWS Bedrock/SageMaker, and Google Cloud Vertex AI.
Experience in data architecture and engineering to support AI initiatives, including data pipelines, feature stores, and data governance.
Experience integrating AI solutions into enterprise systems and applications via APIs, microservices, and event-driven architectures.
Experience with AI governance, responsible AI practices, model risk management, and data privacy/security considerations.
Experience integrating AI/GenAI capabilities with automation platforms (e.g., UiPath, Power Automate) to enable intelligent automation.
Bachelor’s degree in computer science, Engineering, Data Science, or a related field, or foreign equivalent required.
Cloud AI/ML certifications (e.g., AWS Certified Machine Learning, Azure AI Engineer, Google Cloud Professional ML Engineer).
Minimum of 10 years of relevant work experience with 2 years of experience in comparable consulting services.
Strategic mindset and the ability to lead and develop other team members.
Multitask, engage with stakeholders, plan effectively, and consistently achieve operational goals.
Excellent relationship-building abilities.
Ability to collaborate with resources in global delivery model.
Experience in leading programs using Agile and/or hybrid methodologies.
U.S. and Canadian citizens and those authorized to work in the U.S. and Canada are encouraged to apply.

Nice To Haves

MBA or equivalent advanced degree.
Industry-related certification preferred.
Creative problem solver.
Strategic mindset and the ability to collaborate with other team members.

Responsibilities

Architecting, designing, and implementing enterprise-grade AI, Machine Learning, and Generative AI solutions.
Leading technical teams delivering complex AI and automation engagements across industries.
Translating business problems into AI solution architecture using design thinking and structured problem-solving techniques.
Designing AI/ML platform architectures on cloud-native and hybrid environments (AWS, Azure, GCP).
Implementing LLM frameworks and patterns (LangChain, LlamaIndex, Semantic Kernel), vector databases, and Retrieval-Augmented Generation (RAG) architectures.
Applying MLOps/LLMOps practices, including model lifecycle management, CI/CD for ML, monitoring, and retraining pipelines.
Developing AI solutions using Python and ML/AI frameworks such as TensorFlow, PyTorch.
Utilizing cloud AI/ML services such as Azure OpenAI, AWS Bedrock/SageMaker, and Google Cloud Vertex AI.
Designing data architecture and engineering to support AI initiatives, including data pipelines, feature stores, and data governance.
Integrating AI solutions into enterprise systems and applications via APIs, microservices, and event-driven architectures.
Implementing AI governance, responsible AI practices, model risk management, and data privacy/security considerations.
Integrating AI/GenAI capabilities with automation platforms (e.g., UiPath, Power Automate) to enable intelligent automation.
Leading team interactions with clients, including clients at senior levels.
Leading client delivery teams and managing projects to completion.
Establishing a focus area and concentrating deployment and delivery in that area.
Mentoring and developing consultants on delivery teams.
Leading delivery teams effectively, providing direction, guidance, motivation, and course correction.
Supporting development of innovative thinking.
Understanding Infosys Consulting business drivers and KPIs.
Representing Infosys through sales and marketing materials.
Playing a key role in practice or firm-building activities.
Taking bottom-line responsibility for firm building deliverables or activities.
Supporting Associate Partners and Partners in pursuit and proposal work.
Identifying opportunities from client work and relationships and raising them to appropriate Associate Partner or Partner for action.