EnCharge AI

Senior Staff / Principal SOC Floorplan Lead

Bangalore, India · Work style not stated

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About the role

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  • EmployerEnCharge AI
  • LocationBangalore, India
  • Work styleWork style not stated
  • Employer posted

The Role

We are seeking a highly skilled and hands-onSoC Floorplan Leadto own the physical foundation of our next-generation AI and Data Center SoCs. In this critical role, you will be the bridge between architecture, logic design, and physical design. You will work hand-in-hand with Chip Architects and RTL Leads to influence micro-architecture and ensure the physical implementation achieves best-in-class Power, Performance, and Area (PPA).

If you love solving complex spatial puzzles on advanced technology nodes, integrating sensitive analog components, and driving execution in a high-energy start-up environment, this is the role for you.

Key Responsibilities

Top-Level Floorplanning:Own the SoC-level floorplan from concept to tape-out for high-performance, large-scale AI/Data Center chips on advanced process nodes (e.g., 5nm, 3nm or below).

Architecture & RTL Collaboration:Partner closely with Architecture and RTL teams to provide early physical feasibility feedback. Drive block partitioning, shape optimization, and data-flow planning to achieve the absolute best PPA.

Show full description

Bump & Package Co-Design:Lead bump planning and IO ring definition. Work with packaging teams on flip-chip/advanced packaging constraints, ensuring optimal signal escape and power delivery.

Custom & Analog Routing:Manage the placement and custom routing strategies for critical Analog/Mixed-Signal (AMS) IPs, high-speed SerDes (PCIe, Ethernet, Memory interfaces), PLLs, and sensitive clock distributions.

Power Delivery Network (PDN):Design and analyze the top-level power grid, ensuring robust power delivery for high-current AI workloads while minimizing IR drop.

Pin Assignment & Feedthroughs:Manage macro placement, block-level pin assignments, and top-level feedthrough planning to optimize global timing and routing congestion.

Methodology Development:Build and maintain scalable Floorplanning workflows and scripts (Tcl, Python) tailored for a lean, fast-moving start-up team.

Required Skills & Qualifications

Experience:12 + years of hands-on experience in Physical Design SoC Floor planning preferably in Datacenter domain, with at least 3 years acting as a lead or primary owner of SoC-level Floorplanning.

Domain Expertise:Proven track record of taping out large, complex chips—specifically forData Center, Networking, or AI/Machine Learningapplications.

Start-Up Mentality:Highly driven, self-motivated, and comfortable with ambiguity. You take extreme ownership of your domain, pivot quickly when needed, and roll up your sleeves to get things done.

Technical Depth:

Deep understanding of how RTL structures and architectural decisions impact physical design PPA.

Extensive experience with bump planning, flip-chip package requirements, and die-to-package co-optimization.

Strong knowledge of analog/mixed-signal IP integration, shielding, and custom routing constraints.

Expertise with industry-standard physical design tools ( Cadence Innovus).

Education:BS, MS, or Ph.D. in Electrical Engineering, Computer Engineering, or a related field.

Preferred Qualifications

Experience with multi-die / chiplet integration (2.5D, 3D packaging, interposers, UCIe).

Strong scripting and automation skills (Tcl, Python, Perl, Makefile).

Knowledge of advanced clocking architectures (H-trees, meshes) for highly synchronous AI fabrics.

What We Offer

Impact:The opportunity to build ground-up architecture and see your ideas taped out in cutting-edge silicon.

Equity:Competitive start-up equity packages—when the company wins, you win.

Culture:A flat, collaborative, and bureaucracy-free environment surrounded by top-tier industry veterans.

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At a glance

  • SeniorityLead / Principal
  • Employer posted
  • Added to ROLIVA
  • Last checked

Skills in this posting

Skills ROLIVA found in the employer’s own description above. A mention is not a requirement.

Python Machine learning

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