16 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Own the end-to-end architecture and design of optimized GCP compute infrastructure for large-scale AI and machine learning systems.
- Design and tune accelerated compute clusters, distributed training systems, container platforms, model-serving environments, networking, and high-throughput storage.
- Evaluate architecture alternatives across compute, networking, storage, orchestration, observability, security, compliance, cost, and operational complexity.
- Lead architecture reviews and assessments, identify risks and optimization opportunities, and recommend remediation actions.
- Define roadmap inputs, capacity planning models, scaling strategies, cost forecasts, and performance improvements.
- Design deployment automation and CI/CD strategies for AI systems, models, data pipelines, and platform components.
- Establish monitoring and observability practices across infrastructure operations and MLOps, including SLAs, SLOs, alerting, and performance and cost tracking.
- Integrate AI and machine learning systems into enterprise environments while meeting security, compliance, regulatory, and client standards.
- Collaborate with clients, stakeholders, architects, and engineering teams to translate requirements into architecture standards.
- Set technical direction, mentor engineers, review designs and code, and promote engineering best practices.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related engineering field.
- Minimum 7.5 years of experience is required.
- At least 4 years of experience building, monitoring, troubleshooting, designing, and operating AI/ML infrastructure, cloud platforms, data platforms, model deployment pipelines, or large-scale engineering solutions.
- At least 4 years of proficiency with programming or scripting languages such as Python, Java, C++, Bash, PowerShell, or equivalent engineering languages.
- At least 4 years of experience in AI/ML infrastructure engineering or related roles on a hyperscaler or enterprise platform.
- Strong understanding of AI/ML concepts and infrastructure for production AI workloads.
- Experience with data pipeline and workflow management tools such as Apache Airflow, Kubeflow, managed orchestration services, or platform-native workflow tooling.
- Strong hands-on experience with GCP AI infrastructure services including Compute Engine, GKE, Vertex AI, Cloud Storage, Filestore, IAM, VPC, Cloud Build, Cloud Monitoring, and Cloud Logging.
- Experience architecting accelerated compute, distributed training, model serving, high-throughput storage, container platforms, and secure cloud networking.
- Strong working knowledge of Terraform, Docker, Kubernetes, observability, and incident response practices.
- Ability to optimize AI infrastructure for performance, power, cost, scalability, security, reliability, and compliance.
- Experience producing architecture decision records, reference implementations, standards, runbooks, and reusable infrastructure patterns.
- 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.
- Strong problem-solving, communication, collaboration, and stakeholder-alignment skills.
- Preferred qualifications include GCP certifications, industry experience in regulated sectors, exposure to LLM infrastructure and vector databases, retrieval pipelines, accelerator scheduling, high-performance storage, low-latency model serving, model optimization, enterprise architecture governance, FinOps, and infrastructure vendor collaboration.
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About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.