Edge Infra Architect-Specialist Senior

Artificial Intelligence & Engineering

AI & Engineering leverages cutting-edge engineering capabilities to help build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These insights are powered by engineering for business advantage, helping transform mission-critical operations.

Join our AI & Engineering team to help transform technology platforms, drive innovation, and help make a significant impact on our clients' achievements. You'll work alongside talented professionals reimagining and re-engineering operations and processes that could be critical to businesses.

Position Summary

Level: Specialist Senior

As a Specialist Senior at Deloitte Consulting, you will design, develop, and deploy enterprise-scale software solutions, lead the creation of robust pipelines and manage code deployment across environments. You will collaborate with cross-functional, global teams to translate functional requirements into effective deliverables, independently guiding and mentoring junior team members. Your role spans the full project lifecycle, including estimation, planning, execution, and tracking key metrics for analysis, ensuring high-quality and timely delivery of solutions. You will be responsible for individually delivering high quality solutions within due timelines in an agile framework. Need-basis consultants will be mentoring and/or directing junior team members/liaising with onsite/offshore teams to understand the functional requirements.

Work you'll do:

Lead discussions with business and functional analysts to understand requirements and assess integration impacts on business architecture. Prepare technical architecture and design, clarify requirements, and resolve ambiguities. Develop solutions in line with established technical designs, integration standards, and quality processes. Create and enforce technical design and development guides, templates, and standards. Facilitate daily scrum meetings, manage deliverables, and prepare weekly status reports for leadership review. Conduct detailed deliverable reviews and provide technical guidance to team members. Collaborate with onsite clients, coordinators, analysts, and cross-functional teams. Design templates or scripts to automate routine development or operational tasks.

• Reference Architecture: Develop tailored edge computing architectures covering infrastructure, platform, and software stack.
• Stakeholder Engagement: Translate business needs into scalable, secure technical solutions.
• NVIDIA Hardware: Deploy and optimize NVIDIA edge devices (Jetson, EGX, IGX, DGX) for AI performance.
• AI/ML Integration: Architect seamless integration of NVIDIA AI Enterprise stack for efficient AI/ML deployment.
• Fleet Management: Utilize NVIDIA Fleet Command or similar platforms for secure, centralized management of edge device fleets.
• Deployment: Implement and optimize physical and logical edge infrastructures.
• Cloud Integration: Ensure unified data flow and management between edge and cloud environments.
• Automation: Use IaC tools (Ansible, Terraform) for scalable deployment and management.
• Monitoring: Continuously monitor systems for performance and reliability.
• Disaster Recovery: Develop robust strategies for disaster recovery and high availability.
• Security: Enforce strict security and compliance best practices.
• Troubleshooting: Resolve connectivity, hardware, and software challenges at edge sites.
• Mentorship: Guide and mentor junior staff on edge/cloud best practices.

The team:

At Hybrid Cloud Infrastructure, we deliver solutions spanning Hybrid Cloud, Advanced Connectivity, AI Data Centers, High-Performance Computing, and AI Infrastructure to help clients achieve their desired outcomes. Our offerings include engineered transformation services for hybrid cloud infrastructure and platforms, prioritizing resiliency, optimization, and extensive automation. We integrate Advanced Connectivity, with AI Infrastructure and AI to boost operational efficiency and enable real-time data processing, crucial for critical low-latency enterprise operational technology (OT) applications. Additionally, we provide comprehensive management of all facets of operations for hybrid cloud infrastructure and field operations.

Qualifications

Must Have Skills/Project Experience/Certifications:

• 6 - 10 years of hands-on experience in Cloud Platform: Extensive experience with Edge Services/ Platforms offered by at least one of the major cloud providers (AWS, Azure, or Google Cloud), specifically integrating cloud services with NVIDIA edge deployments (e.g., managing edge data flow to AWS S3, Azure Blob Storage, or Google Cloud Storage).
• AI Infrastructure Providers: Experience with leading Edge AI Infrastructure providers, including NVIDIA (DGX, EGX, IGX. Jetson platforms), DELL, HPE, etc.
• Edge Management: Expertise in edge management platforms, including solutions provided by cloud providers (AWS IoT Greengrass, GDCC, Azure IoT Edge) or other solutions offered by infra players such as NVIDIA (Fleet Command/ JetPack/Jetson Run-time, Run.AI), Dell NativeEdge, Red Hat OpenShift (edge), Oracle Rowing Edge etc.
• Containerization and Orchestration: Expertise in containerization technologies like Docker and proficiency in orchestration tools like Kubernetes, specifically deploying containers optimized for GPU utilization using NVIDIA Container Toolkit or Kubernetes operators for NVIDIA GPUs.
• Programming Languages: Proficiency in languages such as Python, Java, C++, or similar, with practical experience in developing or integrating with CUDA-accelerated applications or AI models optimized for edge deployment.
• Infrastructure as Code: Extensive experience with Terraform or similar tools for automating the provisioning and configuration of edge infrastructure, including GPU-enabled nodes.
• Networking: Strong understanding of VPC, subnets, firewalls, TCP/IP, DNS, and load balancing, with experience optimizing network architecture for low-latency edge AI inference and data offloading.
• Security: Knowledge of IAM, encryption, and compliance standards, with experience securing NVIDIA edge devices and managing secure boot/hardware security modules (HSMs).
• Monitoring and Logging: Experience with Stackdriver, Prometheus, Dynatrace, Datadog, ELK, or similar tools, including monitoring GPU metrics (e.g., using NVIDIA DCGM) for performance and reliability.
• Project Management: Proven track record in leading large-scale cloud infrastructure projects, specifically those involving the integration and deployment of AI/ML workloads on edge hardware.
• Collaboration: Effective communicator with cross-functional teams, including network engineers, cloud architects, and data scientists utilizing NVIDIA platforms.

Good to Have Skills/Project Experience/Certifications:

• Problem-Solving: Strong analytical and troubleshooting skills to address client-specific challenges.
• Adaptability: Ability to quickly adapt to changing client requirements and emerging technologies.
• Project Leadership: Demonstrated leadership in managing client projects, ensuring timely delivery and client satisfaction.
• Business Acumen: Understanding of business processes and the ability to align technical solutions with client business goals.

Education:

• BE/B.Tech/M.C.A./M.Sc (CS)/ M. Tech degree or equivalent from accredited university

Location:

• Bengaluru/ Hyderabad

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Benefits to help you thrive

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Requisition code: 317567