A Search and Advisory Firm

Building the teams where models,
hardware, and deployment converge.

Searches

9 closed

in five months, across six functions

Embedded

4070

AI hardware company

Intake to offer

~6 weeks

median across recent searches

Stage

Seed to Series B

as the team, or an extension of it

Coverage

NY · DC · LDN · SF

on-site or remote

§ I.Practice

From research through deployment

01

AI

Research, applied physics, post-training and RL, evals, agents

02

Hardware

Novel compute architecture, silicon design and verification, hardware/software co-design

03

Software

Product, infrastructure, security, reliability, compilers and runtime

04

Deployment

Forward-deployed engineering, field application engineering, deployment strategy

§ II.Selected Work

Recent searches

Role

Focus

Geography

01

Post-Training Lead

RL and reward modeling

New York

02

Silicon Systems Architect

Novel compute architecture

New York

03

Reliability Engineer

Evaluation and regression systems

San Francisco

04

Platform Security Engineer

Secure-by-default infrastructure

US Remote

05

Forward-Deployed Engineer

AI for semiconductor engineering

London

06

Deployment Strategist

Agentic software deployment

New York

§ III.Engagement

One principal, end to end

No handoffs. The person who scopes the role runs the search and closes the hire.

Contingent

One role, or a few. Exclusive.

Retained

Committed on both sides, staged against milestones.

Embedded

Dedicated capacity across a quarter. Operating as part of the team.

Contingent

Retained

Embedded

One role, or a few. Exclusive.

Committed on both sides, staged against milestones.

Dedicated capacity across a quarter. Operating as part of the team.

Every engagement includes role definition, market mapping, interview design, compensation, and offer strategy.

§ IV.Thesis

Computing is being rebuilt across layers

Models shape hardware, hardware shapes product, and deployment shapes what gets built next. The loop keeps tightening.

Teams follow the architecture. ML for chip design connects research to silicon. Agent and platform engineering connects models to production systems. Forward-deployed engineering connects the product to the customer's environment. Each requires context from both sides.

I built Core Operative at that convergence, inside a venture-backed AI hardware company, helping the team grow from 40 to 70. Searches across AI, hardware, software, and deployment, including standing up its FDE function.

Companies move at the speed of their hardest hire.

Devin Sidhu

Principal, Core Operative

LinkedIn ↗X ↗

§ V.Contact

Start with the hardest one.

Taking select searches and embedded engagements.

Direct

Practice

AI · Hardware · Software · Deployment

Coverage

NY · DC · LDN · SF