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Accenture

Advises businesses and runs their technology

AI Infrastructure Architect

Platform EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related engineering field.
  • At least 5 years of experience is stated in the project role description.
  • At least 2 years of experience coding, building, monitoring, or troubleshooting AI/ML infrastructure, data platforms, model deployment pipelines, or cloud/platform engineering solutions.
  • Strong understanding of AI/ML concepts and the compute, storage, networking, security, and deployment foundations required to run AI workloads.
  • At least 2 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash, or PowerShell.
  • Experience with CI/CD, infrastructure-as-code, containers, Kubernetes, workflow orchestration, and operational monitoring tools.
  • Hands-on experience with Snowflake warehouses, databases, schemas, secure data sharing/access controls, Snowpark, Python/SQL workloads, and cloud storage integrations.
  • Experience designing or operating scalable data pipelines, feature-preparation workloads, AI application integrations, and production analytics or ML enablement workloads.
  • Working knowledge of SQL, Python, dbt/Terraform, CI/CD pipelines, data observability, and cost/performance optimization practices.
  • Ability to optimize warehouses, queries, data pipelines, and integrations for performance, reliability, scalability, cost, and security.
  • Understanding of MLOps/data-platform patterns, including feature engineering, model input/output management, monitoring, and governance.

Responsibilities

  • Architect and build custom artificial intelligence infrastructure and hardware solutions.
  • Optimize AI infrastructure and hardware performance, power consumption, cost, and computational-stack scalability.
  • Advise on AI infrastructure technology and vendor evaluation, selection, and full-stack integration.
  • Design, build, automate, monitor, and optimize Snowflake-based AI/ML infrastructure for secure data access, feature preparation, model enablement, AI application integration, and production analytics workloads.
  • Contribute to compute optimization, deployment automation, observability, governance, security, and operational reliability for AI-driven business solutions.
  • Write, review, and debug SQL, Python, scripts, and infrastructure-as-code for Snowflake AI/ML infrastructure, automation, monitoring, and deployment tooling.
  • Configure and manage Snowflake warehouses, databases, schemas, secure access patterns, Snowpark workloads, Streamlit apps, model-related data pipelines, and integrations with cloud storage and orchestration tools.
  • Support deployment automation and CI/CD pipelines for Snowflake-based AI solutions using tools such as Git, Terraform, dbt, Python, containers, and workflow-orchestration tooling where applicable.
  • Deploy and operate data/feature pipelines, AI application integrations, and model-enablement components while applying reliability, security, cost-efficiency, and scalability practices.
  • Monitor warehouse utilization, query performance, pipelines, and integration health; troubleshoot issues across compute, storage, access control, data movement, and application layers.
  • Collaborate with data scientists, ML engineers, data engineers, platform engineers, and architects to integrate Snowflake-enabled AI solutions into enterprise systems while meeting compliance and operational requirements.
  • Document reusable patterns, configuration standards, and runbooks for Snowflake-based AI infrastructure.

Desired Qualifications

  • Snowflake certification such as SnowPro Core, SnowPro Advanced Architect, SnowPro Data Engineer, or related platform credentials.
  • Exposure to industry use cases in BFSI, healthcare, retail/e-commerce, telecom, manufacturing, or public sector where data/AI platforms must meet compliance, reliability, and data-governance expectations.
  • Familiarity with Snowpark, Cortex/AI features, vector search, retrieval pipelines, feature engineering, and model-enablement patterns.
  • Knowledge of data governance, data-sharing controls, FinOps practices, incident management, and production-support processes for enterprise AI platforms.
  • Snowflake Data Warehouse is listed as a good-to-have skill.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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