Get hired atNUMOS AI×The Anti Job Board

How to Actually Get Hired

Who reads applications, which channel gets a reply, and what they screen for.

<50 peopleSan Mateo / San FranciscoAI

What gets their attention

The seed press release and the Axios exclusive both name engineering team expansion as the primary use of capital. The company has nine employees as of early 2026 and is going into an acceleration phase with two major enterprise logos and a seed round from General Catalyst. The engineering roles at numosai.com/careers are described as building "the infrastructure for AI-powered, outcome-oriented platforms." That framing, moving from "workflow-driven systems" to "outcome-oriented platforms", is a significant architectural description. It signals Numos is building agents that don't just execute steps but evaluate whether outcomes are correct, which is an eval-heavy, reinforcement-loop engineering challenge. The Operator Collective co-investor is a network of enterprise go-to-market operators, which means future GTM hires will also come through that network.

Why applying the normal way doesn't work

With only <50 employees, NUMOS AI doesn't have dedicated recruiters. Founders review applications between running the company. The challenge isn't competition — it's visibility. Direct outreach wins.

Who to contact at NUMOS AI

Who decides:a founder or department head
Best channel:LinkedIn or direct email

Founding team

PS
Parijat Sarkar
Co-Founder and CEO

Parijat's background is a study in the specific kind of cross-disciplinary depth that tends to produce good enterprise software founders. He was born in India and grew up in Abu Dhabi, before studying at the University of Pennsylvania and Wharton, which is where his engineering and business foundations formed simultaneously. The Penn/Wharton combination is significant: Penn Engineering produces rigorous computer scientists, while Wharton produces people who think in terms of organisational systems and financial incentives. Parijat absorbed both. He graduated in 2011 with a Bachelor of Engineering, and his early career took him through Microsoft, where he worked in product, before he joined Zenefits. Zenefits at the time was one of Silicon Valley's most scrutinised HR software companies, having gone through a dramatic growth-and-governance crisis before stabilising under new leadership. Parijat rose to Senior Vice President holding leadership responsibilities across product, growth, and engineering simultaneously, a scope that is unusually broad for someone who hadn't yet founded a company, and that reflects both his versatility and the confidence the Zenefits leadership placed in him. After Zenefits he spent time at South Park Commons, the San Francisco founder community and fellowship programme, and at TriNet before going into stealth with Numos. The framing he uses publicly, "finance teams aren't just analyzing numbers, they're accountable for them", is a precise articulation of why auditability is the product's core differentiator, and it is the intellectual entry point for any cold outreach that wants to resonate.

MT
Mitul Tiwari
Co-Founder and CTO

Mitul is one of the more academically and technically decorated CTOs at a seed-stage AI company right now, and his credentials are directly relevant rather than incidentally impressive. He completed his undergraduate degree in Computer Science and Engineering at the Indian Institute of Technology, Bombay, in 2001, ranked 49th among over 100,000 candidates in the IIT-JEE entrance examination that year, placing him in the top 0.05% of all examinees. He also placed in the top 25 students selected for the gold medal of the National Science Enrichment Programme in Physics in 1997. Those early academic signals established a pattern that continued throughout his career: he is someone who operates at the very top of whatever field he enters. He then moved to the University of Texas at Austin for graduate study, receiving both an NSF grant and a Texas Advanced Technology Program grant while completing his PhD in Computer Science in 2007, which focused on distributed systems, caching, and resource scheduling. His co-authored work during this period spans conferences including SPAA and IPDPS. After UT Austin he joined Kosmix, a web-scale text categorisation and entity extraction company that was later acquired by Walmart (becoming Walmart Labs), where he worked on large-scale information retrieval. He then spent years at LinkedIn, where he was Head of People You May Know and Growth Relevance, two of LinkedIn's most critical recommendation systems, each operating at hundreds of millions of users. His published work from this period includes papers at KDD, WWW, RecSys, SIGIR, and CIKM on social recommender systems, entity extraction, and collaborative filtering. He then co-founded Passage AI, a conversational AI company that was acquired by ServiceNow, after which he joined ServiceNow as Director of AI and Machine Learning Engineering, leading their natural language processing group and shipping production features including Conversational AI, Incident Auto Resolution, Question-Answering for Search, and Text2Workflow using LLMs. He received ServiceNow's Advanced Technology Group Team of Excellence award for the Text2Workflow product, which is directly analogous to the workflow automation Numos is building for finance. He has co-authored more than twenty publications across the top AI and data conferences. His personal site is mitultiwari.net. For technical candidates, Mitul is the right person to engage directly with a concrete technical take on multi-agent orchestration for financial workflows.

What to show them

General Catalyst's involvement signals that a Series A conversation is likely within 18 months. The data that will drive that conversation is ARR growth, customer expansion, and a replicable sales motion. Right now Parijat is carrying the commercial narrative personally, which is appropriate at seed but does not scale. A revenue operations or GTM lead who can build the commercial infrastructure, ICP definition, outreach sequencing, deal tracking, customer success metrics, before the Series A process starts is the hire that makes the difference between a clean process and a scrambled one. Operator Collective's network of enterprise GTM operators is likely the sourcing channel for this hire. Core skills: enterprise GTM strategy, revenue operations, CRM build-out (HubSpot or similar), ICP analysis, outbound sequencing, SaaS metrics fluency, CFO-level communication comfort. Proof of work: Map three ICPs for Numos, different by company stage, industry, and finance stack complexity, and write one paragraph on the buying motion and outreach angle for each. Show that you understand why a Series B fintech and a mid-market manufacturing company have different decision-making processes for AI finance tools. Send to Parijat.

A cold email that works at NUMOS AI

Subject: GTM / Revenue Operations Lead, [your one-line proof]
Hi Parijat, I mapped three distinct ICPs for Numos, each with a different finance stack, company stage, and buying motion, and wrote out how the sales narrative differs across them. One angle that felt underexplored is the public company segment, where audit trail requirements make Numos's transparency positioning especially strong. Happy to share the full breakdown.

What NUMOS AI screens for

What they look for: The seed press release and the Axios exclusive both name engineering team expansion as the primary use of capital. The company has nine employees as of early 2026 and is going into an acceleration phase with two major enterprise logos and a seed round from General Catalyst. The engineering roles at numosai.com/careers are described as building "the infrastructure for AI-powered, outcome-oriented platforms." That framing, moving from "workflow-driven systems" to "outcome-oriented platforms", is a significant architectural description. It signals Numos is building agents that don't just execute steps but evaluate whether outcomes are correct, which is an eval-heavy, reinforcement-loop engineering challenge. The Operator Collective co-investor is a network of enterprise go-to-market operators, which means future GTM hires will also come through that network.

Tailor your CV to the specific NUMOS AI role rather than sending a general one. Applications that mirror the language of the job description clear automated filters at a materially higher rate.

Mistakes that kill applications

Don't send the same CV you sent everywhere else. At <50 people it's obvious, and it's the fastest rejection there is.

Lead with their problem, not your ambition. NUMOS AI is focused on General Catalyst does not often lead seed rounds — show you understand that.

Most AI applications get ghosted. A day-five follow-up can double your response rate.

Frequently asked questions

How do I apply to NUMOS AI?

Through the roles on our NUMOS AI jobs page, or directly to a founder or department head if you can reach them. At <50 people, direct outreach outperforms the form.

Does NUMOS AI respond to cold emails?

We haven't verified response rates at NUMOS AI yet.

Who is the hiring manager at NUMOS AI?

At this size, hiring is usually run by a founder or department head.

How competitive is it to get hired at NUMOS AI?

Roles at <50-person AI companies typically draw 50-100 applicants in the first two weeks. Applying inside 72 hours of a posting going live is the single biggest lever you control.

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