EdgeAI Architect

Capgemini; Bengaluru; On-site; INR 1,800,000 - 2,600,000; Full time

Job summary

Capgemini Bengaluru is seeking an Edge AI Solution Architect to lead the design, development and deployment of AI/ML on embedded and edge computing platforms.

You will partner with customers, product teams and engineering to architect scalable Edge AI solutions that maximize performance, power efficiency and deployment scalability, while leveraging hardware accelerators such as GPU, NPU and DSP across NVIDIA Jetson, NXP i.MX and Qualcomm ecosystems.

Qualifications

• 11+ years in Embedded Systems, AI/ML Engineering, or Product Engineering.
• Proven AI/Edge AI model development, optimization and deployment.
• Experience with embedded AI platforms like NVIDIA Jetson, NXP i.MX, Qualcomm.
• Experience leveraging hardware accelerators (GPU, NPU, DSP, TPU).

Responsibilities

• Lead the architecture and implementation of Edge AI and Embedded AI solutions across a wide range of intelligent products and devices.
• Define end-to-end AI deployment strategies for embedded and edge computing environments.
• Architect AI/ML solutions on leading embedded platforms including NVIDIA Jetson, NXP i.MX, Qualcomm AI platforms, or equivalent ecosystems.
• Leverage hardware acceleration technologies including GPU, NPU, DSP, and AI accelerators to maximize inference performance and efficiency.

Job description

As an Edge AI Solution Architect, you will lead the design, development, and deployment of AI/ML solutions on embedded and edge computing platforms. You will work closely with customers, product teams, and engineering organizations to architect scalable Edge AI solutions that leverage hardware accelerators while maximizing performance, power efficiency, and deployment scalability.

In this role, you will:

• Lead the architecture and implementation of Edge AI and Embedded AI solutions across a wide range of intelligent products and devices.
• Define end-to-end AI deployment strategies for embedded and edge computing environments.
• Architect AI/ML solutions on leading embedded platforms including NVIDIA Jetson, NXP i.MX, Qualcomm, and similar edge computing ecosystems.
• Leverage hardware acceleration technologies including GPU, NPU, DSP, and AI accelerators to maximize inference performance and efficiency.

Your Profile

• 11+ years of experience in Embedded Systems, AI/ML Engineering, or Product Engineering.
• Proven expertise in AI and Edge AI model development, optimization, and deployment.
• Strong experience with embedded AI platforms such as NVIDIA Jetson, NXP i.MX, Qualcomm AI platforms, or equivalent ecosystems.
• Experience leveraging hardware accelerators such as GPU, NPU, DSP, TPU, and dedicated AI processing engines.