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.
Level: Lead Cloud Integrated Infrastructure Engineer II
As a Lead Cloud Integrated Infrastructure Engineer II at Deloitte Consulting, you will help clients apply physical AI and spatial technologies to operational environments such as data centers, sports venues, and consumer or retail settings. You will translate business and operational needs into scalable architecture, platform, and transformation solutions across NVIDIA, Google Cloud Platform, and Amazon Web Services ecosystems. This role combines client-facing solution design, delivery leadership, and hands-on technical direction across the project lifecycle. You will also support proposal efforts, guide multidisciplinary teams, and help deliver measurable outcomes for complex transformation programs.
Work you'll do
As a Lead Cloud Integrated Infrastructure Engineer II on the Hybrid Cloud Infrastructure team, you will be responsible for…
- Leading end-to-end physical AI delivery, from synthetic data generation and simulation-based policy training through hardware commissioning and production deployment.
- Partnering with sales and customer success teams to scope engagements, lead technical discovery workshops, and develop reference architectures and proof-of-concept deliverables.
- Driving platform selection decisions across simulation, perception, robot orchestration, and edge compute, including documenting trade-offs and presenting recommendations to senior stakeholders.
- Connecting spatial engineering and physical AI engineering efforts to align simulation outputs, autonomy development, and deployed system performance.
- Building reusable architecture patterns, blueprints, and best practices across NVIDIA Omniverse, Isaac, Metropolis, and partner ecosystems.
The team
Deloitte’s AI & Engineering practice helps clients build, deploy, and operate integrated solutions across software, data, artificial intelligence, networks, and hybrid cloud infrastructure. Within Hybrid Cloud Infrastructure, the team delivers solutions spanning hybrid cloud, advanced connectivity, AI data centers, high-performance computing, and AI infrastructure to help clients achieve targeted business outcomes. The practice focuses on resiliency, optimization, automation, and operational performance across infrastructure platforms and field operations. Team members work across engineering, connectivity, and AI-enabled infrastructure to support real-time processing and critical operational technology environments.
Location: Hyderabad/Bengaluru
Shift Timings: As per Business Requirements
Qualifications
Required:
- 8-12+ years of experience in consulting, industry, or a combination of both.
- Experience aligned to NVIDIA and/or Google Cloud Platform or Amazon Web Services ecosystems for physical AI and spatial AI, including technologies such as Omniverse, Cosmos, Isaac, Metropolis, Jetson, Orin, NeMo, Groot, Google Distributed Cloud Edge, Anthos, Vertex AI, TensorFlow, Immersive Stream, Earth Engine, Gemini, Agent Builder, Amazon Outposts, Elastic Kubernetes Service, SageMaker, AppStream, and Bedrock.
- Experience leading end-to-end physical AI delivery, including simulation-based training, synthetic data generation, hardware integration, and production deployment on robot platforms.
- Experience with NeRFStudio and 3D Gaussian Splatting, including capture and processing of real-world scans and maintenance of Universal Scene Description export pipelines in Nucleus.
- Experience architecting and training 3D perception models, including point-cloud networks, spatial transformers, and implicit neural representations.
- Experience with motion planning tools such as MoveIt 2, CuRobo, and Isaac Manipulator.
- Experience with simultaneous localization and mapping tools such as ORB-SLAM3, LIO-SAM, or RTAB-Map.
Preferred:
- Consulting experience in client-facing strategy, architecture, or transformation delivery roles.
- Experience in data center, sports venue, consumer, or retail environments.
- Experience with hardware calibration, including intrinsic and extrinsic camera calibration, LiDAR-camera extrinsic estimation, and sensor noise characterization.
- Experience with hand-eye calibration, including calibration rig setup, integration into ROS 2 TF trees, and end-effector accuracy validation.
- Experience with sim-to-real transfer methods, including fidelity gap metrics, distribution shift analysis, domain randomization, and transfer learning.
- Experience optimizing edge inference for 3D perception using TensorRT, INT8 or FP16 quantization, and CUDA kernels on Jetson hardware.
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