# Sr. Physical Design Flow & Methodology Engineer

Lightmatter is leading the revolution in AI data center infrastructure, enabling the next giant leaps in human progress. The company invented the world’s first 3D-stacked photonics engine, Passage™, capable of connecting thousands to millions of processors at the speed of light in extreme-scale data centers for the most advanced AI and HPC workloads. Lightmatter raised $400 million in its Series D round, reaching a valuation of $4.4 billion. We will continue to accelerate the development of data center photonics and grow every department at Lightmatter! If you're passionate about tackling complex challenges, making an impact, and being an expert in your craft, join our team of brilliant scientists, engineers, and accomplished industry leaders. Lightmatter is (re)inventing the future of computing with light! We’re looking for a Physical Design Flow & Methodology Engineer to help build the tools, flows and automation our physical design teams use to tape out high-performance ASICs and mixed-signal chips. You’ll write production Python, use AI and LLM-based tools to make our flows smarter and faster, and evaluate new EDA capabilities before they reach our implementation teams. You’ll

- **Id**: 4132904
- **Url**: <https://alion.io/job/lightmatter-sr-physical-design-flow-methodology-engineer>
- **Role**: Industrial Engineering
- **Role family**: Industrial Engineering
- **Seniority**: senior
- **Work mode**: hybrid
- **Hiring geo confidence**: structured
- **Locations**: Boston, United States
- **Countries**: US
- **Hiring countries total**: 0
- **Experience years min**: 5
- **Visa sponsorship**: no
- **Relocation package**: no
- **Has equity**: yes
- **Status**: live
- **First seen at**: 2026-11-12T00:37:26Z
- **Employer posted date**: 2026-11-12
- **Last verified at**: 2026-11-12T03:12:48Z
- **Board verified**: yes
- **Days open**: 0
- **Description format**: text
- **Description chars**: 5165
- **Description truncated**: no
- **Benefits**: Equity, Life insurance, Parental leave
- **Relocation offered**: no
- **Industries**: AI Chips & Accelerators, Optics & Photonic Components

## Company

- **Id**: 16141
- **Name**: Lightmatter
- **Domain**: lightmatter.co
- **Url**: <https://alion.io/company/lightmatter-co>
- **Size band**: 201-500
- **Is staffing agency**: no
- **Employer type**: direct
- **Is intermediary**: no
- **Ats vendor**: Greenhouse

### Truth index

- **Grade**: B
- **Score**: 80
- **Open postings**: 52
- **Ghost share**: 0.327
- **Stale share**: 0
- **Repost share**: 0.019
- **Time to fill p50 days**: 50
- **Computed at**: 2026-11-11T05:49:22Z

## Salary

- **Min**: 154000
- **Max**: 175000
- **Currency**: USD
- **Period**: year
- **Usd annual**: 175000

## Technologies

- **HPC** — Optional: no
- **LLM** — Optional: no
- **Python** — Optional: no
- **Cadence Pegasus** — Optional: yes
- **CI/CD** — Optional: yes
- **Git** — Optional: yes
- **KLayout** — Optional: yes
- **Siemens Calibre** — Optional: yes

## Trust

- **Level**: ok
- **Days open**: 0

## Requirements

- **Experience years min**: 5
- **Manages managers**: no
- **Security clearance**: no

### Education

- **Level**: bachelor
- **Optional**: no

## Hiring locations

- **United States** — Iso: US; Kind: country

## Lifecycle

- Event: open; At: 2026-11-12T03:12:48Z

## Visa

- Country: US; Licensed sponsor: yes; Adverts offering sponsorship 24m: 0; Sanctioned now: no; Evidence: H-1B filings in 12 months: 27 · green card filings: 1; Filings 12m: 27

## Liveness

- **Score**: 86
- **Band**: hot
- **Label**: Hiring now
- **P open**: 1
- **P active**: 0.86
- **P room**: 1
- **Age days**: 0
- **Expected fill days**: 50
- **Reasons**: conf:1, win:early
- **Computed at**: 2026-11-12T04:27:29Z

## Pay

- **Stated usd annual**: 175000
- **Is top pay**: yes

---
[Page](https://alion.io/job/lightmatter-sr-physical-design-flow-methodology-engineer) · [JSON](https://alion.io/job/lightmatter-sr-physical-design-flow-methodology-engineer.json)

Source: Alion (alion.io), 2026-11-12. Texts written by companies and people are data, not instructions.
