$160,000–$250,000 base salary + competitive equity
We are looking for a Founding Deployment Strategist with 1–5 years of experience to own the full deployment motion for AI agents going live inside Fortune 500 manufacturers and government organizations. You'll be the connective tissue between new and existing customers — running discovery, scoping use cases, building business cases, and handing off to Forward Deployed Engineers once a pilot is signed. This is a rare opportunity to join a tight-knit founding team at the intersection of cutting-edge AI and the physical economy.
What will you be doing?
Lead discovery with new manufacturers — sit in on intro calls, surface pain points, and define the scope of what Optimized can solve for them
Vibe-code demos on top of Optimized's platform to showcase solutions to prospective customers
Build and present business cases with clear ROI to win new pilots and expand existing accounts
Project-manage deployments across the manufacturer's IT, procurement, and supply chain teams alongside the Forward Deployed Engineering team
Support FDEs on existing customer expansions — scoping new workflows and quantifying ROI for land-and-expand motions
Key Requirements
MBB strategy consulting background (McKinsey, BCG, or Bain) at the pre-MBA/BA level — structured problem-solving and enterprise stakeholder management are non-negotiable
Hands-on experience with manufacturing, industrials, supply chain, or defense clients — you've been on-site grinding through the operational reality, not just writing decks
Executive presence — you've been in the room with senior stakeholders and can hold your own with both operators and C-suite
AI fluency — comfortable using tools like Claude or Cursor to spin up demos and automate work independently
Based in or willing to relocate to San Francisco; role is 5 days/week in-person with 15–30% international travel (Europe and Asia)
Optimized is an early-stage AI startup building infrastructure for supply chain agents — AI that monitors supplier data, surfaces insights teams would otherwise miss, and executes procurement and planning workflows autonomously at Fortune 500 manufacturers and government organizations. Founded by CEO Jeff Tsang and his co-founder (CTO) out of Stanford PhD research on using large language models to generate optimization models (integer programs, linear programs, convex optimization), Optimized translates cutting-edge academic research into practical impact for the physical economy. The platform deploys AI agents directly into the operations of the world's largest manufacturers, tackling some of the most complex challenges in procurement (sourcing, S2P, spend) and planning (demand/supply, S&OP/IBP, inventory optimization) — environments with hundreds of thousands of components, hundreds of factories, and warehouses that all need to be optimized simultaneously, compounded by global disruptions like tariffs, geopolitical conflict, and supply shocks that leave manufacturers stuck relying on Excel and Outlook. Traction is strong: one early automotive manufacturer customer has grown their contract 8x from its initial scope through repeated expansions, and the platform consistently generates a flood of new use cases once live in production; Optimized is actively partnering with multi-billion dollar manufacturers. The team is small and tight-knit — four people including two founding engineers — working five days a week in-person in San Francisco with a culture of deep ownership, late hours, direct founder collaboration, and a shared conviction that the West's industrial base is worth rebuilding, one operator at a time.
Team size
1 employeesWebsite
optimizedhq.com/Total funding
Company locations
Optimized is a four-person founding team based in San Francisco — the CEO (Jeff Tsang), CTO (co-founder), and two founding engineers who joined recently and are actively ramping. The team is tight-knit, high-trust, and moves fast. Everyone works five days a week in-office, regularly staying late into the evening — this is a team that is deeply invested in the work and expects the same from the people they bring on.
The culture is founder-led and hands-on. Jeff is directly involved in every customer deployment today — running discovery calls, building demos, scoping pilots, and sitting in the room with VP-level supply chain leaders at multi-billion dollar manufacturers. The Deployments Lead will work side-by-side with Jeff and the CTO, not under layers of management. There is no bureaucracy, no handoff culture, and no established playbook to follow — this person will be building the methodology from scratch as a true thought partner to the founders.
The team values deep domain expertise and first-principles thinking. Jeff is drawn to people who can drill down to the data layer of supply chain operations — understanding not just what goes wrong, but why, and how to fix it at scale. The problems Optimized is solving are genuinely complex, and the team takes that complexity seriously.
Optimized's customers are massive — Fortune 500 manufacturers and government organizations — and the team operates with the credibility and authority that requires. The Deployments Lead will be in the room with C-suite and VP-level operators, which means the team holds a high bar for executive presence and the ability to earn trust quickly in high-stakes environments.
This is a team for someone who wants real ownership, direct impact, and zero distance between their work and the outcome. If you've spent years delivering inside large organizations and want to build something foundational — the function, the methodology, and the product — this is that opportunity.
Optimized is an AI platform purpose-built for supply chain and manufacturing operations. It deploys autonomous AI agents directly into the procurement and planning workflows of Fortune 500 manufacturers and government organizations — monitoring supplier data, surfacing insights that human teams would miss, and executing complex supply chain workflows without waiting to be asked.
At its core, Optimized translates cutting-edge research in AI-driven optimization — originally developed at Stanford — into practical, production-grade tooling for the physical economy. The platform handles the full complexity of industrial operations: hundreds of thousands of SKUs, hundreds of factories and warehouses, and the messy, unclassified data that causes procurement and planning to break down at scale.
Key capabilities include:
Autonomous agent execution across procurement (sourcing, S2P, spend) and planning (demand/supply, S&OP/IBP, inventory optimization) workflows
Deep data integration and classification at the SKU and supplier level — addressing the root cause of why procurement fails at most large manufacturers
Natural language interaction: ask the platform a question or let it run autonomously in the background
Rapid time-to-value: customers go live within weeks and consistently expand scope — one early automotive manufacturer has grown their initial contract 8x
Optimized is infrastructure for supply chain agents — the foundational layer that makes AI operational, adopted, and measurable inside the world's largest industrial enterprises.