The Role
Architect and implement AWS-based AI/ML data platform infrastructure including compute, storage, networking, orchestration, model serving, observability and cost optimization. Lead architecture decisions, create IaC/CI-CD patterns, prototype GPU/distributed training environments, run assessments, mentor architects, and provide executive technical advisory to deliver production-ready, secure and scalable AI platforms.
Summary Generated by Built In
Project Role : Data Platform Architect
Project Role Description : Architects the data platform blueprint and implements the design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
Must have skills : AWS AI Services
Good to have skills : AI Agents & Workflow Integration
Minimum 18 year(s) of experience is required
Educational Qualification : 15 years full time education
Role Summary / Description
AI Powered Tech Talent
As an Technical Architect in AI Infrastructure Architecture , you will act as a senior technical authority for AWS-based AI/ML compute infrastructure, shaping the technical vision, reference architecture, standards and implementation strategy for large-scale AI systems. You will evaluate complex choices across compute, networking, storage, orchestration, model serving, observability, security and cost optimization, while guiding senior and lead architects/Technical Architects to deliver resilient, scalable and production-ready AI infrastructure. You will bring industry experience across enterprise AI adoption, compliance, reliability, FinOps and platform modernization to help clients translate AI infrastructure trade-offs into measurable business value.
Key Responsibilities
Set the overarching AWS AI infrastructure vision, strategy and reference architecture for large-scale AI/ML systems, including compute, networking, storage, orchestration, model serving and observability.
Own complex architectural decisions across AWS services such as EC2, EKS, SageMaker, S3, FSx/EFS, VPC, IAM, CloudWatch and related DevOps/security tooling, rationalizing options against client standards and business objectives.
Architect and prototype cost-optimized GPU/accelerated compute and distributed training environments, building benchmarks, proof-of-concepts and reusable implementation patterns.
Define architecture standards, reusable infrastructure-as-code patterns, CI/CD approaches, model deployment patterns, monitoring strategy, SLAs/SLOs and cost/performance governance for production AI/ML systems.
Lead architecture assessments and design reviews validate findings through hands-on implementation, profiling, performance tuning and troubleshooting across the AI infrastructure stack.
Evaluate emerging AI infrastructure technologies, accelerators, interconnects, managed AI services and ecosystem tools, and recommend where they belong in enterprise solutions.
Provide executive and client-level technical advisory, translating cloud infrastructure trade-offs into clear, defensible recommendations connected to business outcomes.
Mentor architects and Technical Architects, build community best practices and represent the practice in internal and external technical forums.
Required Qualifications
Bachelor's degree in Computer Science, Computer Technical Architecting, Information Technology or a related Technical Architecting field.
Minimum 6 years of experience coding, building, monitoring, troubleshooting, designing and operating AI/ML infrastructure, cloud platforms, data platforms, model deployment pipelines or large-scale Technical Architecting solutions.
Strong understanding of AI/ML concepts and the compute, infrastructure, orchestration and deployment foundations required to run production AI systems.
Minimum 6 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash, PowerShell or equivalent Technical Architecting languages.
Experience with data pipeline and workflow management tools such as Apache Airflow, Kubeflow, managed orchestration services or platform-native workflow tooling.
Proven experience leading AI infrastructure projects and teams, including technical direction, design reviews, delivery governance and stakeholder alignment.
Strong project management, communication, problem-solving and cross-functional collaboration skills in fast-paced client or enterprise environments.
Demonstrated experience evaluating and selecting AI technologies, frameworks, reference architectures and platform services for production solutions.
Required Skills/ Experience
Expert-level hands-on architecture experience with AWS AI infrastructure services including EC2, EKS, SageMaker, S3, IAM, VPC, CloudWatch and automation/DevOps services.
Deep knowledge of GPU/accelerated compute, distributed training, model serving, container platforms, storage design, network design, observability and resilience Technical Architecting.
Strong experience with Terraform/CloudFormation, CI/CD, Docker, Kubernetes, security guardrails, monitoring and infrastructure cost optimization.
Ability to evaluate multiple AWS architecture options and produce standards, patterns, decision records, benchmarks and executive-ready recommendations.
Experience applying MLOps/InfraOps practices for experiment tracking, model registry, deployment automation, monitoring, incident response and rollback strategies.
Good to Have Skills
AWS certifications such as Solutions Architect Professional, DevOps Technical Architect Professional or Machine Learning specialty/associate credentials.
Industry experience designing AI infrastructure for BFSI, healthcare, retail/e-commerce, telecom, manufacturing, energy or public sector environments with compliance, security and reliability constraints.
Exposure to LLM infrastructure, vector databases, retrieval pipelines, GPU scheduling, model optimization, high-performance storage and low-latency model serving.
Experience with enterprise architecture governance, technology roadmaps, vendor/partner management, FinOps and production support operating models.15 years full time education
Project Role Description : Architects the data platform blueprint and implements the design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
Must have skills : AWS AI Services
Good to have skills : AI Agents & Workflow Integration
Minimum 18 year(s) of experience is required
Educational Qualification : 15 years full time education
Role Summary / Description
AI Powered Tech Talent
As an Technical Architect in AI Infrastructure Architecture , you will act as a senior technical authority for AWS-based AI/ML compute infrastructure, shaping the technical vision, reference architecture, standards and implementation strategy for large-scale AI systems. You will evaluate complex choices across compute, networking, storage, orchestration, model serving, observability, security and cost optimization, while guiding senior and lead architects/Technical Architects to deliver resilient, scalable and production-ready AI infrastructure. You will bring industry experience across enterprise AI adoption, compliance, reliability, FinOps and platform modernization to help clients translate AI infrastructure trade-offs into measurable business value.
Key Responsibilities
Set the overarching AWS AI infrastructure vision, strategy and reference architecture for large-scale AI/ML systems, including compute, networking, storage, orchestration, model serving and observability.
Own complex architectural decisions across AWS services such as EC2, EKS, SageMaker, S3, FSx/EFS, VPC, IAM, CloudWatch and related DevOps/security tooling, rationalizing options against client standards and business objectives.
Architect and prototype cost-optimized GPU/accelerated compute and distributed training environments, building benchmarks, proof-of-concepts and reusable implementation patterns.
Define architecture standards, reusable infrastructure-as-code patterns, CI/CD approaches, model deployment patterns, monitoring strategy, SLAs/SLOs and cost/performance governance for production AI/ML systems.
Lead architecture assessments and design reviews validate findings through hands-on implementation, profiling, performance tuning and troubleshooting across the AI infrastructure stack.
Evaluate emerging AI infrastructure technologies, accelerators, interconnects, managed AI services and ecosystem tools, and recommend where they belong in enterprise solutions.
Provide executive and client-level technical advisory, translating cloud infrastructure trade-offs into clear, defensible recommendations connected to business outcomes.
Mentor architects and Technical Architects, build community best practices and represent the practice in internal and external technical forums.
Required Qualifications
Bachelor's degree in Computer Science, Computer Technical Architecting, Information Technology or a related Technical Architecting field.
Minimum 6 years of experience coding, building, monitoring, troubleshooting, designing and operating AI/ML infrastructure, cloud platforms, data platforms, model deployment pipelines or large-scale Technical Architecting solutions.
Strong understanding of AI/ML concepts and the compute, infrastructure, orchestration and deployment foundations required to run production AI systems.
Minimum 6 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash, PowerShell or equivalent Technical Architecting languages.
Experience with data pipeline and workflow management tools such as Apache Airflow, Kubeflow, managed orchestration services or platform-native workflow tooling.
Proven experience leading AI infrastructure projects and teams, including technical direction, design reviews, delivery governance and stakeholder alignment.
Strong project management, communication, problem-solving and cross-functional collaboration skills in fast-paced client or enterprise environments.
Demonstrated experience evaluating and selecting AI technologies, frameworks, reference architectures and platform services for production solutions.
Required Skills/ Experience
Expert-level hands-on architecture experience with AWS AI infrastructure services including EC2, EKS, SageMaker, S3, IAM, VPC, CloudWatch and automation/DevOps services.
Deep knowledge of GPU/accelerated compute, distributed training, model serving, container platforms, storage design, network design, observability and resilience Technical Architecting.
Strong experience with Terraform/CloudFormation, CI/CD, Docker, Kubernetes, security guardrails, monitoring and infrastructure cost optimization.
Ability to evaluate multiple AWS architecture options and produce standards, patterns, decision records, benchmarks and executive-ready recommendations.
Experience applying MLOps/InfraOps practices for experiment tracking, model registry, deployment automation, monitoring, incident response and rollback strategies.
Good to Have Skills
AWS certifications such as Solutions Architect Professional, DevOps Technical Architect Professional or Machine Learning specialty/associate credentials.
Industry experience designing AI infrastructure for BFSI, healthcare, retail/e-commerce, telecom, manufacturing, energy or public sector environments with compliance, security and reliability constraints.
Exposure to LLM infrastructure, vector databases, retrieval pipelines, GPU scheduling, model optimization, high-performance storage and low-latency model serving.
Experience with enterprise architecture governance, technology roadmaps, vendor/partner management, FinOps 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
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Skills Required
- Minimum 18 years of experience
- 15 years full time education
- Bachelor's degree in Computer Science or related field
- Minimum 6 years building, operating or architecting AI/ML infrastructure, cloud platforms, data platforms or model deployment pipelines
- Minimum 6 years proficiency in programming or scripting (Python, Java, C++, Bash, PowerShell)
- Expert-level hands-on architecture experience with AWS services (EC2, EKS, SageMaker, S3, IAM, VPC, CloudWatch) and AWS AI Services
- Experience with infrastructure-as-code (Terraform, CloudFormation), CI/CD, Docker and Kubernetes
- Experience with data pipeline and workflow tools (Apache Airflow, Kubeflow)
- Deep knowledge of GPU/accelerated compute, distributed training, model serving, storage and network design, observability and resilience
- Experience applying MLOps/InfraOps practices (experiment tracking, model registry, deployment automation, monitoring, incident response)
- Proven experience leading AI infrastructure projects and teams with strong communication and stakeholder alignment
- Ability to evaluate AWS architecture options and produce standards, benchmarks and executive recommendations
Accenture Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Accenture and has not been reviewed or approved by Accenture.
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Healthcare Strength — Pay is considered competitive when paired with robust insurance options and other perks that compare well with large consulting and IT services peers. Multiple national medical plan options plus dental and vision are positioned as a core strength of the overall package.
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Retirement Support — Retirement support is positioned as a standout feature through a 401(k) dollar-for-dollar match up to a set percentage after eligibility. The package is reinforced by additional financial programs such as savings tools and related resources.
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Parental & Family Support — Parental and caregiving supports are presented as a meaningful benefit differentiator through substantial paid parental leave and multiple caregiver-oriented programs. Backup care and fertility/adoption/surrogacy navigation and reimbursements add breadth to family support beyond leave alone.
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The Company
What We Do
Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services—all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 500,000+ people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com.
