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Open nowPosted 280 days ago

Founding Full-Stack Engineer - Takt

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San Francisco Bay Area
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Your applicationOpen nowFounding Full-Stack Engineer - TaktPear VC · San Francisco Bay Area
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13.7% of postings close within 7 days. Measured by our own scanner across the market. Pear VC postings stay open a median of 13 days.

Share of postings closed within
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  2. 4.7%3 days
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  4. 22.1%14 days
  5. 37.8%30 days
  6. 59.1%60 days
This job: posted 280 days ago

Pear VC median: 13 days open

The posting

ABOUT TAKT

Our Vision: A world where factories think.

Takt is building the brains of factories.

Factories have spent the last decade digitizing: adding sensors, software, and

dashboards everywhere. Yet most factories aren’t meaningfully smarter. Data is

fragmented across disconnected systems, locked in reports, and dependent on tribal

knowledge living in people’s heads.

The hard problem isn’t collecting data, it’s turning it into institutional intelligence.

Takt is building the brains of factories. We’re closing the loop from data → information

→ insight → action by orchestrating AI agents with deep operational context across

the entire manufacturing stack. These systems reason about what’s happening, why it’s

happening, and what to do next, acting as a continuous thought partner to factory

leadership across sales, operations, supply chain, and finance.

This is not a chatbot or another analytics layer. We’re pushing the frontier of AI

reasoning and decision-making in real-world, high-stakes environments. Just as Tesla

redefined the car as a software-first system, Takt is redefining manufacturing as a

software-defined industry.

FUNDING

Takt is funded by Pear VC (backed Doordash, Gusto) and is part of the

PearX accelerator program.

Website: www.taktconnect.com http://www.taktconnect.com

FOUNDERS

Takt was founded by Adhitya Raghavan (CEO) and Will Zunker (CTO).

Adhitya is from a small village in South India and first learned about factories by working

as an operator on his father’s shop floor. His journey through squash took him to

Princeton (Mechanical & Aerospace Engineering), Harvard (MBA, Baker Scholar), and

Bain. Now, he’s bringing it full circle, building Takt to solve the very pain he experienced

firsthand in factories and aiming to put a dent in the $8 trillion of waste that occurs in

manufacturing globally.

Will an MIT PhD has deep experience in optimizing manufacturing processes through

physics-based modeling and AI, driven by a belief that advanced methods can

fundamentally transform how things are made. Along the way, he built open-source

tools and collaborated with engineers across diverse manufacturing sectors, learning

firsthand the challenges of waste and inefficiency on the factory floor. Now, at Takt, he’s

channeling that journey into building technology that helps factories run smarter, faster,

and with less waste.

CORE CULTURAL VALUES

1. Stupid enough to make our dreams a reality: We are dreamers who build a better world. We own our decisions. We have the irrational belief and hunger to work until our dreams are a reality

2. The last one standing: Every single person takes ownership of their work with a gritty resourcefulness and dares to fight for it with every ounce of their energy.

3. Insatiable curiosity: Its always day 1 and we are an empty cup, a dry sponge ready to learn. Approaching every action with humility and scientific rigor and adopting a Kaizen mindset.

4. The best F1 team in the stadium: We win together and lose together; every person plays a crucial role to win the race. We have high expectations, trust our teammates and create the environment for everyone to shine. In the path the victory, we celebrate every small professional and personal win cherishing the journey

ROLE

Founding Full Stack Engineer

- Location: San Francisco, in person 4 to 5 days a week. Open to candidates willing to relocate.

- Hours: 50 to 70 hours per week with space for personal interests

- Compensation: 120-180K

- Equity: To be discussed (0.5-1%)

- Prior experience: 2-3 years minimum

You will be the first engineering hire and will work directly with the founders to build the

core intelligence engine that powers modern factories. You will help design, build, and

deploy systems across the entire stack and influence the earliest product, infrastructure,

and architecture decisions. This role is for someone who wants deep ownership and

real long-term impact.

CORE TECHNICAL REQUIREMENTS

- Experience deploying and maintain full stack production grade code at scale to support 50-100 enterprise customers with minimal downtime

- Strong cloud infrastructure skills (Azure preferred).

- Deep experience with data pipelines, especially cleaning messy, inconsistent real-world data AI-native in approach to coding utilizing new-age tools (e.g. Claude Code) to develop with speed.

- Strong generalist coding skillset especially on the back-end side.

NICE TO HAVE

- Experience shipping production AI/ML or LLM systems end-to-end (not research prototypes).

- Comfortable owning LLM tool orchestration, chain design, agent delegation, prompt engineering, and evaluation methodology.

- Hands-on experience integrating with enterprise systems like ERP, MES, and other data historians (Microsoft Business Central/ SAP)

- Working knowledge of relational + SQL databases

- Familiarity with per missioning models, data governance, or SOC2/GDPR.

- Experience engaging with IT teams and meeting security requirements for enterprise customers.

MINDSET & WORK STYLE

- Strong sense of agency and ownership: comfortable making fast decisions and revising them.

- Shipping and moving quickly, makes practical choices, and delivers value to customers

- Willing to learn and can get things done, even if they don’t know it from the get-go

- Thrives with incomplete information

- Passion for the product: speaks their mind, contributes ideas, and pushes for the best solution

- Long-term commitment to the mission, we are building foundational systems, not short-lived features. This means putting in the hours consistently and also making harder short term decisions for long term benefits

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