Sr. Manager, Physical Design Engineering, Annapurna Labs

Job description

Annapurna Labs, designs custom silicon powering AWS’s cloud infrastructure. Custom SoCs live at the heart of Amazon ML servers — including Inferentia and Trainium Systems — delivering high-performance ML inference and training at cloud scale.

We’re looking for a Senior Manager, Physical Design Engineering to build and lead a world-class Physical Design team delivering multi-billion-transistor ML accelerator SoCs on latest tech nodes.

This is a player-coach role

you will personally engage in the most critical technical decisions; chip-level floorplan architecture, multi-GHz timing convergence, high-speed I/O physical design, power delivery for KW class systems, and 2.5D / 3D integrations; while building a high-performing team and driving rigorous PPA targets, first-pass silicon success, and relentless continuous improvement.

Key job responsibilities

- Build, hire, and develop a physical design team of 10-15 engineers. Own headcount planning, performance management, career growth, and organizational scaling to support multiple concurrent tapeouts.

- Own the physical design strategy and execution roadmap across Inferentia, Trainium, and future products: implementation architecture, hierarchical methodology, PPA target-setting, and technology node adoption.

- Institutionalize continuous PPA improvement: benchmarking frameworks, regression tracking, design-quality dashboards, post-tapeout retrospectives, and structured improvement programs that compound across generations.

- Provide hands-on technical leadership on the hardest problems: multi-GHz timing closure, PDN architecture, high-speed I/O physical design, and 2.5D / 3D cross-die integration.

- Lead technology node enablement for 2nm and beyond: PDK evaluation, reference flow development, PPA pathfinding, and adoption recommendations.

- Define and deploy innovative RTL2GDS methodologies and CAD flows. Champion AI/ML-augmented design automation (RL-placement, ML-guided ECO, predictive analytics). Optimize cloud infrastructure for PD compute.

- Serve as part of senior technical interface with foundry partners and EDA vendors on tool roadmap, co-development, and technology co-optimization.

- Own tapeout execution: readiness reviews, foundry submittal, mask data coordination, and post-silicon yield learning. Drive cross-functional alignment with RTL, DFT, STA, Package, and Validation teams.