AI Infrastructure Architect
Accenture
- Location
- Onsite (Bengaluru, Karnataka)
- Employment
- Full-time
- Level
- Senior Level
Posted 5 days ago
About the role
Accenture is seeking an AI Infrastructure Architect to research and prototype advanced AI techniques, converting validated methods into production-quality libraries and services for enterprise agentic systems.
Skills
Large Language Models
Python
Machine Learning
Deep Learning
Statistics
Experimental Design
Foundation Models
Agentic Systems
Claude Code
Codex
Cursor
Hugging Face
Weights & Biases
MLflow
LangSmith
Infrastructure Architecture
Full job details
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 : Large Language Models (LLMs)
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Conduct applied AI research and convert promising techniques into robust components for enterprise agentic systems and AI products.
Advanced use of Claude Code, Codex, Cursor, Hugging Face, Weights & Biases, MLflow and LangSmith to accelerate experiment implementation, benchmark creation and failure analysis while preserving reproducibility, versioning, statistical validity and production-quality code.
Must show evidence of applied research reaching deployed products, platforms, or production pilots. Purely paper-oriented research or notebook-only experimentation is insufficient.
Roles & Responsibilities:
- Research and prototype techniques in reasoning, planning, memory, retrieval, evaluation, adaptation, or multimodal AI.
- Design reproducible experiments and meaningful benchmarks.
- Compare models and approaches across quality, latency, cost, safety, and scalability.
- Convert validated methods into production-quality libraries and services.
- Partner with architects and engineers on deployment and operational hardening.
- Investigate production failures and improve system behavior.
- Mentor research engineers and contribute to patents or publications where relevant.
Professional & Technical Skills:
- Machine learning, deep learning, statistics, and experimental design.
- Advanced Python and modern model-development frameworks.
- Foundation models, agentic systems, evaluation, and behavior analysis.
- Reliable, testable, and maintainable production code.
15 years full time education
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 : Large Language Models (LLMs)
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Conduct applied AI research and convert promising techniques into robust components for enterprise agentic systems and AI products.
Advanced use of Claude Code, Codex, Cursor, Hugging Face, Weights & Biases, MLflow and LangSmith to accelerate experiment implementation, benchmark creation and failure analysis while preserving reproducibility, versioning, statistical validity and production-quality code.
Must show evidence of applied research reaching deployed products, platforms, or production pilots. Purely paper-oriented research or notebook-only experimentation is insufficient.
Roles & Responsibilities:
- Research and prototype techniques in reasoning, planning, memory, retrieval, evaluation, adaptation, or multimodal AI.
- Design reproducible experiments and meaningful benchmarks.
- Compare models and approaches across quality, latency, cost, safety, and scalability.
- Convert validated methods into production-quality libraries and services.
- Partner with architects and engineers on deployment and operational hardening.
- Investigate production failures and improve system behavior.
- Mentor research engineers and contribute to patents or publications where relevant.
Professional & Technical Skills:
- Machine learning, deep learning, statistics, and experimental design.
- Advanced Python and modern model-development frameworks.
- Foundation models, agentic systems, evaluation, and behavior analysis.
- Reliable, testable, and maintainable production code.
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
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