Director Engineering - AI software stack

Overview

Director of Engineering for an AI software stack, owning AI/ML technology strategy and leading end-to-end delivery of AI systems from research to production.

What you'll do

• Define and own AI/ML technology roadmap across automotive and edge AI platforms.
• Drive adoption of LLMs, VLMs/LVMs, multimodal AI, and agentic AI for safety-critical deployments.
• Oversee end-to-end delivery of AI systems, including model onboarding, optimization, validation, and lifecycle management.
• Ensure performance targets (power, latency, memory, accuracy) across heterogeneous compute (CPU/GPU/DSP/NPU).
• Establish best practices for model optimization (quantization, compression, batching, KV-cache tuning, mixed precision).
• Build, mentor, and scale multi-disciplinary AI/ML engineering teams and set technical direction.

What you'll need

• Experience requirement: 25+ years of industry experience in software engineering (as stated).
• People management: 20+ years of people management experience, including managing managers or senior technical leads and customers (as stated).
• Programming experience: 2+ years with programming languages such as C, C++, Java, Python (as stated).
• Minimum education/experience options: Bachelor’s with 3+ years, or Master’s with 2+ years, or PhD with 1+ year in software engineering (as stated).
• Strong background in AI/ML system design, including edge/embedded deployment.
• Hands-on experience with ML frameworks (PyTorch, TensorFlow, ONNX) and edge/embedded deployment.
• Ability to deliver large-scale, production AI systems in complex environments.

Details

• Location: Bangalore, India.