AI Infrastructure Architect

8109 ASOL-Chennai SEZ Company; Chennai District; On-site; INR 2,800,000 - 3,600,000; Full time

Job summary

Accenture is hiring an AI Infrastructure Architect to lead end-to-end Snowflake data and AI infrastructure design for production ML applications. You will architect scalable warehouses, Snowpark workloads, AI-enabled pipelines and governance, with a focus on performance, security and cost efficiency.

You will mentor engineers, drive CI/CD for AI infra, and collaborate with clients to ensure architectural alignment with SLAs and standards.

Qualifications

• Bachelor's degree in CS/CE/IT or related field.
• Minimum 4 years delivering AI/ML infra, cloud and data platforms.
• Strong knowledge of AI/ML concepts and deploy/operate infra.
• Proficient in Python/Java/C++ and scripting languages.
• Experience with data pipelines and orchestration tools.

Responsibilities

• Own end-to-end Snowflake data and AI infra architecture.
• Design scalable warehouses, Snowpark workloads and data pipelines.
• Lead deployment, automation and CI/CD for AI systems.
• Establish monitoring, security, compliance and cost controls.
• Collaborate with clients and teams to translate requirements into architecture.

Skills

Machine Learning

Python

Java

C++

Bash

PowerShell

SQL

Problem-solving

Communication

Education

Bachelor's degree in CS/CE/IT

15 years full time education

Tools

Snowflake

Azure Data Services

Airflow

Kubeflow

Snowpark

Cortex/AI capabilities

Streamlit

Terraform

Job description

Project Role : AI Infrastructure Architect Project Role Description : Architect and build custom Artificial Intelligence (AI) infrastructure/hardware solutions. Optimize AI infrastructure/hardware performance, power consumption, cost and scalability of computational stack. Advise on AI infrastructure technology and vendor evaluation, selection and full stack integration. Must have skills : Machine Learning (ML) Good to have skills : Snowflake Data Warehouse, Microsoft Azure Data Services Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education AI Powered Tech Talent Role Summary / Description

As a Senior Engineer in AI Infrastructure Architecture for Snowflake, you will own significant portions of the end-to-end architecture and engineering of optimized data and AI infrastructure for production machine learning and AI-enabled applications. You will design scalable warehouses, Snowpark workloads, AI-ready data/feature pipelines, model-enablement patterns, automation and operational controls that align with client standards, SLAs, security, compliance and cost-efficiency expectations. You will bring industry experience across enterprise AI adoption, platform modernization, regulated data workloads, FinOps and production reliability, while mentoring engineers and partnering with architects to translate business requirements into robust Snowflake-based AI infrastructure solutions.

Key Responsibilities

• Own end-to-end architecture and design of optimized Snowflake data and AI infrastructure, including 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, Streamlit applications and cloud integrations, including compute sizing, query optimization, governance, access controls and high-throughput data access design.
• Serve as an authoritative AI infrastructure expert on Snowflake, applying deep knowledge of Snowflake Data Cloud capabilities, data/AI application patterns, governance, security and cost levers.
• Develop and evaluate architecture alternatives, weighing trade-offs across compute, networking, storage, orchestration, model serving, observability, security, compliance, cost and operational complexity.
• Lead architecture assessments and reviews of existing and proposed environments, identifying gaps, risks, bottlenecks and optimization opportunities, and recommending remediation actions.
• Drive architecture decision-making by documenting rationale, trade-offs, assumptions and dependencies so decisions are transparent, defensible and aligned with business SLAs and standards.
• Define and maintain AI infrastructure roadmap inputs, capacity planning models, scaling strategies, cost forecasts and performance improvement opportunities.
• Design deployment, automation and CI/CD strategies for reliable, repeatable and scalable releases of AI systems, models, data pipelines and platform components into production.
• Establish AI monitoring and observability practices across InfraOps and MLOps, including SLAs, SLOs, alerting, performance/cost tracking and continuous optimization.
• Integrate AI/ML systems into enterprise environments while ensuring interoperability, security, compliance, regulatory alignment and adherence to client standards.
• Collaborate with clients, stakeholders, architects and engineering teams to align infrastructure decisions with business outcomes and translate requirements into actionable architecture standards.
• Set technical direction for workstreams, mentor engineers, review designs/code and promote engineering best practices across the team.

Required Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Information Technology or a related engineering field.
• Minimum 4 years of experience coding, building, monitoring, troubleshooting, designing and operating AI/ML infrastructure, cloud platforms, data platforms, model deployment pipelines or large-scale engineering solutions.
• Strong understanding of AI/ML concepts and the computing infrastructure required to deploy, run and optimize production AI workloads.
• Minimum 4 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash, PowerShell or equivalent engineering languages.
• Experience with data pipeline and workflow management tools such as Apache Airflow, Kubeflow, managed orchestration services or platform-native workflow tooling.
• Strong problem-solving skills and ability to work in a fast-paced engineering or client delivery environment.
• Excellent communication, collaboration and stakeholder alignment skills.
• Minimum 4 years of experience in AI/ML infrastructure engineering or related roles on a hyperscaler or enterprise platform for deploying large-scale solutions.
• Proven experience leading AI projects or engineering workstreams and managing priorities across multiple initiatives.
• Demonstrated experience evaluating and selecting AI technologies, frameworks, cloud services and architecture patterns.

Required Skills/ Experience

• Strong hands-on experience with Snowflake warehouses, databases, schemas, secure data sharing/access controls, Snowpark, Cortex/AI capabilities, Streams/Tasks, Streamlit and cloud ecosystem integrations.
• Experience architecting scalable data and feature pipelines, AI application integrations, model-enablement patterns, governance, query/warehouse optimization and secure data access.
• Strong working knowledge of SQL, Python, dbt/Terraform, CI/CD, DataOps, MLOps/AI enablement patterns, observability and incident response practices.
• Ability to optimize Snowflake AI infrastructure for performance, cost, scalability, security, reliability and compliance.
• Experience producing architecture decision records, reference implementations, standards, runbooks and reusable platform patterns.

Good to Have Skills

• Snowflake certifications such as SnowPro Advanced Architect, SnowPro Advanced Data Engineer or related AI/data platform credentials.
• Industry experience in BFSI, healthcare, retail/e-commerce, telecom, manufacturing, energy or public sector environments where data/AI platforms must meet compliance, security, reliability and cost-control requirements.
• Exposure to Snowpark, Cortex/AI features, vector search, retrieval pipelines, feature engineering, model enablement and AI application architecture.
• Knowledge of Snowflake governance, secure data sharing, FinOps, infrastructure partner/vendor collaboration and production support operating models.
• 15 years full time education

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com

Bring your incredible skills and join our global team of innovators. We come together from different backgrounds across the world and work with the latest technologies to create value and growth for our clients. With us, you’ll continue to learn and grow so you can advance in your career. Your personal dreams and ambitions are just as important to us; that’s why we offer support any way we can—when you thrive, we all thrive. Explore your next step at Accenture Belong. Grow. Thrive. Join a great place to work for reinventors who drive meaningful change for our clients, communities, and the world. Wo rld. Explore your next step at Accenture

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