AI Infrastructure Architect

Intro: Senior AI Infrastructure Architect responsible for architecting and building end-to-end AI/data infrastructure and hardware solutions (Snowflake-focused) to enable production machine learning and AI-enabled applications. Role reports into AI Infrastructure Architecture and is a full-time on-site role based in Chennai. Core responsibilities: - Own end-to-end architecture and engineering of Snowflake-based data and AI infrastructure: warehouses, Snowpark workloads, secure data architecture, AI-ready feature/data pipelines, model integration and AI application enablement. - Design and tune scalable Snowflake warehouses, tasks, streams, Snowpark services, Cortex/AI capabilities and Streamlit applications, including compute sizing, query optimization, governance, access controls and high-throughput data access. - Evaluate architecture alternatives and trade-offs across compute, networking, storage, orchestration, model serving, observability, security, compliance, cost and operational complexity. - Lead architecture assessments/reviews, identify gaps/risks/bottlenecks, recommend remediation and document architecture decision records, trade-offs, assumptions and dependencies. - Define capacity planning, scaling strategies, cost forecasts, AI infrastructure roadmaps and performance improvement opportunities. - Define deployment, automation and CI/CD strategies for releases of AI systems, models, data pipelines and platform components; establish monitoring/observability (SLAs/SLOs, alerting, performance/cost tracking). - Integrate AI/ML systems into enterprise environments ensuring interoperability, security, compliance and regulatory alignment; collaborate with clients and stakeholders and mentor engineers. Required qualifications and experience: - Bachelor's degree in CS, Computer Engineering, IT or related engineering field. - Listed experience on the posting includes header: 10-12 years (the posting also states "Minimum 12 year(s) of experience is required"). Required qualifications further list minimums of 4 years for specific infrastructure and coding experience. - Minimum multi-year hands-on experience building, operating and optimizing AI/ML infrastructure, cloud and data platforms, model deployment pipelines and large-scale engineering solutions. - Minimum 4 years proficiency in programming/scripting (Python, Java, C++, Bash, PowerShell) and experience with data pipeline/workflow tools such as Apache Airflow or Kubeflow. - Proven experience leading AI projects or engineering workstreams and evaluating/selecting AI technologies, frameworks and cloud services. Good-to-have / domain experience: - Snowflake certifications (SnowPro Advanced Architect, SnowPro Advanced Data Engineer). - Industry experience in BFSI, healthcare, retail/e-commerce, telecom, manufacturing, energy or public sector; exposure to FinOps, secure data sharing, vector search, retrieval pipelines and model enablement patterns. Notes: Location is Chennai; employment type Full-time. The posting emphasizes Snowflake expertise, production reliability, governance, security, cost-efficiency and mentoring/technical leadership.