---
title: 'Founding Account Executive (Product - Watcher) at Apollo Research'
canonical: 'https://feeny.ai/job/founding-account-executive-product-watcher-apollo-research-london-p80z8e5srm9w'
type: 'job'
last_seen: '2026-11-03'
---

# Founding Account Executive (Product - Watcher) at Apollo Research

- **Company:** Apollo Research
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-23
- **Last confirmed live:** 2026-11-03
- **Apply:** https://jobs.lever.co/apolloresearch/008a594d-0b50-4f15-be9d-ad0a44767cb3

## Job description

## THE OPPORTUNITY

We are building Watcher, a coding agent security product. Watcher is deployed in production and monitors billions of agent tokens per month across engineering teams at agent-building scale-ups and multinational enterprises. We are hiring our founding Account Executive. You will own the sales cycle from qualified interest to signed contracts and build the playbook the rest of the GTM team runs on. Our deals start with a security champion: a principal security engineer or director of product security who has seen what coding agents do inside their org and wants Watcher. Deals are won by taking that champion's interest and moving it through the rest of their organisation to a committed evaluation: the platform team that thinks it could build this itself, the CISO who has to sponsor it, the procurement and legal functions that have to let it in. That handoff, including the build-vs-buy conversation, is where deals stall today. Running it well is the core of this job. We are hiring forward-deployed engineers (FDEs) who run the technical evaluation with you. You own the commercial thread: who needs to say yes, what the evaluation has to prove, and how it converts. You'd work closely with our GTM lead and GTM associate who owns the top of the funnel.

## KEY RESPONSIBILITIES

Convert a champion into an evaluation

- Find the champion in each qualified account, arm them with what they need to sell internally, and map who else has to say yes.
- Run the build-vs-buy conversation with platform and security engineering teams on its merits: what they would have to build, maintain and be on the hook for, against what Watcher already does.
- Secure an executive sponsor and convert interest into a scoped proof of value (POV) with success criteria agreed up front.

Run evaluations to a decision, with FDEs

- Partner with FDEs on technical evaluations. They run the technical work; you keep the evaluation pointed at the decision: momentum, stakeholder coverage, and the commercial case.
- Build the commercial and ROI case that secures executive-level investment.
- Own commercial negotiation, security review, procurement and close in multi-stakeholder cycles involving security, engineering, procurement, legal and executive decision-makers.

Create the way in

- Identify warm introductions paths via investors, advisors, clients, partners and networks. Brief connectors and draft the messaging that makes the introduction land.
- Capitalise on high-value engagement opportunities: speaking panels, hosted roundtables, buyer communities and embedded partners.
- Work with the GTM team on targeted outbound into segments where we have something specific to offer.

Build the playbook and hire the team

- Write down what works: qualification criteria, discovery questions, the build-vs-buy argument, POV structure, pricing guidance, objection handling, security questionnaire answers.
- Report on pipeline health, stage conversion and what is working well enough to double down on.

Product and market insights

- Bring honest signals back about why deals progress or stall, and what buyers compare us against when they consider building it themselves.
- Work with the product team on positioning, pricing, and the collateral enterprise buyers actually ask for.

## REPRESENTATIVE PROJECTS

- Turn a champion into a buyer. Take an account where a principal security engineer loves the product and nothing has moved for two months. Map who else needs to say yes, run the build-vs-buy conversation with the platform team, get an executive sponsor, and convert it into a scoped evaluation with success criteria and a date.

- Compress the cycle. Enterprise evaluations in this market routinely take longer than they need to. Take the process apart with the FDEs,  work out where the time actually goes, and rebuild it so an evaluation reaches a decision faster.

- Land a lighthouse enterprise. Take a large, slow, security-conscious organisation from first conversation through technical evaluation, security review and procurement to a production contract, and turn the process into a documented path the next one can follow.
- Write the playbook. By the time we add the next two people to this team, the thing that gets them productive in a month rather than six should be something you wrote

## JOB REQUIREMENTS

Must-haves

- 5+ years in GTM, with a track record of closing five- and six-figure ACV technical deals as an AE into engineering or security organisations. You have personally taken a technical champion's interest through the rest of their org to a signed contract, and you have won the build-vs-buy argument more than once. Proven success selling a technical product to technical buyers matters more to us than total AE tenure.

- Early-stage experience. You have sold at an early-stage company before it had a machine.You have 2+ years in a startup without mature marketing, no SDR team, no brand recognition doing the work for you. You generated your own pipeline, decided what to work on, and wrote down what worked.

- Technical credibility with a technical buyer. Our buyers are directors of product security, principal security engineers and engineering leaders. You can run discovery with them, understand the architecture well enough to be useful  and know when to bring in an FDE.

Strong nice-to-haves

- You have closed into large, slow organisations. Our pipeline includes banks, quant funds and enterprise technology companies. You have run deals through security review, architecture review and procurement, and have a realistic sense of how long that takes and how to compress it.
- You have sold security, developer tools, or infrastructure.
- Non-linear background. Former founder, operator, or a hybrid role that combined selling with product or strategy.

Explicitly not required

- Formal AI safety background. We need an excellent seller who can learn the AI safety context, and we will teach you what you need to know.
- Management experience. This starts as an individual contributor role.

## BENEFITS

- This role offers market competitive salary, equity, and competitive benefits.

- Base Salary: £85,000 - £129,000; Variable: performance incentives against ARR targets

- Everyone at Apollo effectively has an unlimited token budget. If a better result costs more compute, use it.

- Flexible work hours and schedule

- Unlimited vacation

- Unlimited sick leave

- Up to 6 months of paid parental leave

- Comprehensive health, dental and vision insurance

- Retirement savings with competitive employer matching

- Lunch, dinner, and snacks are provided for all employees on workdays

- Paid work trips, including staff retreats, business trips, and relevant conferences

- A yearly $1,000 (USD) professional development budget

- Relocation support and visa fees (if applicable)

## LOGISTICS

- Time Allocation: Full-time

- Location: This is an in-person role working out of our London office, with regular travel to conferences and customer sites. We offer flexible working hours and some wfh arrangements.

- Visa sponsorship: We sponsor visas in the UK. Sponsorship isn't guaranteed for every role or candidate, but if we make you an offer, we'll work with you to find the right visa route.

## ABOUT THE TEAM

You will work directly with Kyle Dai, our GTM lead and GTM associate on the pipeline, as well as the FDEs we're hiring to run the technical evaluations alongside you. Marius Hobbhahn (CEO) advises the team. You will also interact with our other SWEs and researchers, since we intend to be "our own customer" by using our products internally for our research work. You can find our full team here.

## ABOUT APOLLO RESEARCH

The rapid rise in AI capabilities offers tremendous opportunities, but also presents significant risks. At Apollo Research, we're primarily concerned with risks from Loss of Control, i.e. risks coming from the model itself rather than e.g. humans misusing the AI. We're particularly concerned with deceptive alignment / scheming, a phenomenon where a model appears to be aligned but is, in fact, misaligned and capable of evading human oversight. We work on the science of scheming, detection of scheming (e.g. building evaluations), and scheming mitigations (e.g. anti-scheming). We also work on control and monitoring research (see our scalable monitoring agenda). We work closely with many frontier AI companies, such as OpenAI, Anthropic, Google, Meta, Thinking Machines and others, e.g. to test their models and collaborate on the science of scheming. At Apollo, we aim for a culture that emphasizes truth-seeking, being goal-oriented, giving and receiving constructive feedback, and being friendly and helpful. If you're interested in more details about what it's like working at Apollo, you can find more information here. We also build a coding agent security product called Watcher that secures agent deployments in companies. Our goal is to reduce the probability of catastrophic incidents by securing coding agents, learning about their real-world risks, and publishing our research on how to build these control systems most effectively. Equality Statement: Apollo Research is an Equal Opportunity Employer. We value diversity and are committed to providing equal opportunities to all, regardless of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation.

## HOW TO APPLY

Please complete the application form with your CV. The provision of a cover letter is neither required nor encouraged. Please also feel free to share links to relevant work samples, including anything you have written. About the interview process: Our multi-stage process includes a screening interview, a take-home exercise (2-3 hours), 2-3 technical interviews, and a final interview with Marius (CEO). If you want to prepare, we suggest using a coding agent heavily for a week and forming your own view on who should be buying something like Watcher, and why. Your Privacy and Fairness in Our Recruitment Process: We are committed to protecting your data, ensuring fairness, and adhering to workplace fairness principles in our recruitment process. To enhance hiring efficiency, we use AI-powered tools to assist with tasks such as resume screening. These tools are designed and deployed in compliance with internationally recognized AI governance frameworks. Your personal data is handled securely and transparently. All resumes are screened by a human and final hiring decisions are made by our team. If you have questions about how your data is processed or wish to report concerns about fairness, please contact us at info@apolloresearch.ai.

## About Apollo Research

## Company Overview
- **One-liner**: Apollo Research is an AI safety organization dedicated to securing frontier AI systems by detecting and preventing scheming (deceptive alignment) through technical research, evaluations, monitoring products, and policy guidance.
- **Entity Type**: Private (Public Benefit Corporation)
- **Headquarters**: London, United Kingdom (with offices in San Francisco, California, and opening Washington, D.C.)
- **Founded**: 2023
- **Founders**: Not publicly available from sources

## Core Business
- **Primary industry**: AI safety research and assurance; security monitoring for AI agents
- **Target customers**: Frontier AI developers (e.g., OpenAI, major labs), governments and international bodies, enterprises deploying AI agents
- **Mission**: "Secure frontier AI systems across development, deployment, and governance" [apolloresearch.ai/about](https://www.apolloresearch.ai/about)

## Products & Services
- **Scheming Evaluations**: Behavioral and interpretability-based evaluations to detect whether frontier AI models exhibit deceptive alignment (scheming). Apollo runs these evaluations in partnership with major AI labs, including OpenAI, to assess models before public deployment. [apolloresearch.ai/about](https://www.apolloresearch.ai/about)
- **Watcher (Monitoring Product)**: A two-part product for controlling and securing coding agent deployments:
  - *Watcher Live* – Real-time monitor that identifies and blocks undesirable actions or steers agents back on track.
  - *Watcher Analyze* – Observability layer for reviewing all agent activity, analyzing failures, and receiving notifications. [apolloresearch.ai/blog](https://apolloresearch.ai/blog/apollo-update-may-2026)
- **Governance Advisory & Policy Playbooks**: Threat modeling, loss‑of‑control playbooks, and policy recommendations for governments (e.g., EU AI Office, US Congress, UN Advisory Body). Notable outputs include *The Loss of Control Playbook* and the *Behind Closed Doors* primer on internal deployment. [apolloresearch.ai/blog](https://apolloresearch.ai/blog/apollo-update-may-2026)

## Market Standing
- **Valuation**: Not publicly available
- **Key Metric**: Headcount of 28 employees (as of mid‑2026), growing 72% year‑over‑year [linkedin.com](https://linkedin.com/company/apollo-research-ai)
- **Notable Investors/Partners**: OpenAI (partnered for testing o1 and anti‑scheming interventions), EU AI Office, UN Advisory Body, US Congress [apolloresearch.ai/about](https://www.apolloresearch.ai/about)
- **Growth Signals**: Opened San Francisco office in 2026 with plans to grow to 10+ staff; opening Washington, D.C. office in June 2026; expanding from evals into a full “Science of Scheming” research agenda and a commercial monitoring product [apolloresearch.ai/blog](https://apolloresearch.ai/blog/apollo-update-may-2026)

## Competitive Advantages
- **Unique focus on “scheming”**: Apollo is one of the few organizations dedicated specifically to detecting and preventing deceptive alignment—a risk many labs now acknowledge.
- **First-mover evidence**: Published the first public evidence that frontier models can scheme in context, lending credibility and urgency to their work.
- **Deep lab partnerships**: Direct collaborations with frontier AI developers (e.g., OpenAI) allow Apollo to run pre‑deployment evaluations and influence safety practices.
- **Dual research‑product model**: Combining fundamental behavioral research with a commercial monitoring product (Watcher) creates a real‑world feedback loop and diversified funding.

## Strategic Focus
- **Science of Scheming**: Understanding how scaling trends (e.g., increased situational awareness, long‑horizon RL) drive scheming behavior in future models, rather than only evaluating current models.
- **Evaluation campaigns**: Running suites of behavioral and interpretability tests across frontier models to generalize findings from individual systems.
- **Monitoring productization**: Scaling Watcher as an enterprise tool for securing coding agents, with both immediate safety and long‑term oversight subversion use cases.
- **Policy influence**: Advising governments on loss‑of‑control, internal deployment, and automated AI R&D risks; establishing a D.C. presence to shape national security procurement and regulation.

## Why Work Here
- **Mission‑driven**: Employees work directly on preventing one of the most severe risks from advanced AI—scheming and loss‑of‑control [apolloresearch.ai/careers](https://www.apolloresearch.ai/careers).
- **Compensation**: Competitive salary, equity, pension/401(k) matching, visa sponsorship, and relocation support [apolloresearch.ai/careers](https://www.apolloresearch.ai/careers).
- **Culture**: In‑person collaborative culture with offices in London, San Francisco, and D.C. – “the best collaboration happens in person,” though flexible working hours and work‑from‑home days are offered [apolloresearch.ai/careers](https://www.apolloresearch.ai/careers).
- **AI‑native engineering**: Fluency with AI tools and coding agents is valued; the company expects an engineering mindset and real‑world production skills.
- **High impact**: Small, fast‑growing team (28 people) with outsized influence on frontier AI policy and lab safety practices.

## Sources
1. [apolloresearch.ai/about](https://www.apolloresearch.ai/about)
2. [apolloresearch.ai/careers](https://www.apolloresearch.ai/careers)
3. [linkedin.com](https://linkedin.com/company/apollo-research-ai)
4. [apolloresearch.ai/team](https://www.apolloresearch.ai/team)
5. [apolloresearch.ai/blog](https://apolloresearch.ai/blog/apollo-update-may-2026)

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