We Are

Accenture is helping companies use generative AI to reinvent their enterprise and optimize business functions for breakthrough innovation and competitive advantage. With over 1,600 professionals dedicated to generative AI, leveraging the depth and experience of more than 40,000 AI and data professionals across the company our brings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem.

You Are

An Infrastructure Performance Optimization Engineer who specializes in specializes in executing migration projects related to infrastructure version upgrades, changes in platform(s), service locations or operating entity. You architect and build new infrastructure environments, and understand cost drivers for execution timelines, seeking to optimize business impact and transition speed.

The Work

We are seeking a highly skilled and motivated AI Infrastructure Engineer to join our dynamic team. This role is responsible for ensuring the optimal performance and efficiency of our organization's AI infrastructure systems including quantum computing. You will be accountable for designing, engineering and scaling a cloud infrastructure for operating large scale enterprise class AI applications. You will work closely with cross-functional teams to design, implement and operate scalable, performant, and highly reliable AI systems, while configuring right infrastructure options and services to align with our business objectives.

Position Responsibilities:

• Develop and execute a comprehensive capacity engineering and optimization strategy for Accenture's AI infrastructure performance, including system tuning, resource allocation, workload balancing, and configuration optimization.
• Develop and implement scalability strategies to support our AI growth and changing business requirements.
• Collaborate with cross-functional teams to forecast future infrastructure needs, plan for growth, and ensure scalability by recommending hardware and software upgrades or architectural changes.
• Establish best practices for AI infrastructure management and capacity engineering, fostering a culture of continuous improvement.
• Design and execute stress tests against targeted performance, scale and availability SLAs.
• Troubleshoot performance challenges of the Gen AI platform infrastructure end to end including deployed compute options, network elements, service configurations and storage choices.
• Conduct root cause analysis and provide infrastructure recommendations.
• Conduct technical and cost analysis for making decisions about the right infrastructure options for different workloads and applications for a Gen AI platform.
• Conduct tests for benchmarking and decisioning of different infrastructure choices.
• Design, configure and test appropriate compute options (including serverless) for development, training and inferencing generative ai workloads.
• Design and configure appropriate containerization solutions for Gen AI applications.

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Here's What You'll need

• Minimum of 5 years of hands-on experience in engineering, monitoring and managing hybrid infrastructure with at least one of AWS, GCP or Azure clouds for large scale DL and ML applications.
• Minimum of 3 years of experience performance engineering machine learning solutions on cloud working with different infrastructure options, e.g., GPU clusters
• Minimum of 6 years comprehensive knowledge of compute, storage, networking, quantum computing, and services from cloud providers such as AWS, GCP, or Azure,
• Minimum of 5 years' experience with designing and optimizing deployment infrastructure for developing and deploying open-sourced deep learning models, e.g. from Hugging Face
• Minimum of 6 years of proven experience in management and monitoring tools, infrastructure cost and security services on at least one of the leading clouds
• Minimum 6 years' experience of programming in at least one of the languages Python, Java, or Scala
• Minimum 5 years of strong working knowledge of leading machine learning libraries and frameworks e.g., Xgboost, Sklearn, TensorFlow, PyTorch, etc.
• Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must have minimum 6 years work experience)

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired in Albany County, NY, California, Colorado, New York City or Washington as set forth below.

California $131,100 to $302,400

Colorado $131,100 to $261,300

New York - Albany $121,400 to $241,900

New York City $151,800 to $302,400

Washington $139,600 to $278,200

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Inclusion and diversity are fundamental to our culture and core values. Our rich diversity makes us more innovative and more creative, which helps us better serve our clients and our communities.

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