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Applications deadline: We accept submissions until 15 January 2026. We review applications on a rolling basis and encourage early submissions.
About The Opportunity
We’re looking for Full‑stack Software Engineers who are excited to build tools for frontier AGI safety research, e.g. building and maintaining evals libraries and tools for monitoring and controlling our own LLM traffic.
Representative Projects
* LLM‑powered search that finds interesting fragments in evaluation transcripts
* Comparison views that show how conversations and scores differ between two evaluation runs
* Ability to view and analyse conversations with coding agents (Cursor, Claude Code, etc.) in addition to evaluation transcripts
* Results streaming for evaluations that are currently being run
* Collaborative editing of evaluation logs that automatically updates metrics and other derived data – think of this as developing an “IDE for evaluations”
Besides this, here are example auxiliary projects which you might do:
Key Requirements
* Automated evaluation pipelines to minimize the time from getting access to a new model for pre‑deployment testing to analyzing the most important results and sharing them.
* LLM agents and MCP tools to automate internal software engineering and research tasks, with sandboxes to prevent major failures.
* Telemetry API and instrumentation of our existing tools, allowing us to monitor usage and improve reliability.
* Upstream improvements to the Inspect framework and ecosystem, e.g. support for evaluating modern agentic scaffolds.
Key Responsibilities
* Balance between moving quickly and creating robust and performant software.
* Lead the development of major features from ideation to implementation.
* Support the entire user journey from running the evaluation to finding interesting results to analysing the results to producing reports and papers.
* Make the software configurable and extensible, so that users can adapt it for their needs.
* Collaboratively define and shape the software roadmap and priorities.
* Establish and advocate for good software design practices, codebase health, and coding agent practices.
* Work closely with researchers to understand what challenges they face.
* Work closely with the product team to create solutions that satisfy both our researchers and external customers.
* You must have experience writing production‑quality Python and React code.
* We value candidates from diverse backgrounds and recognise that candidates may demonstrate their skills in different ways. For example, we might be impressed if you have:
o Led the development of a successful software tool or product over an extended period (e.g. 1 year or more).
o Started and built the tech stack for a company, e.g. in a start‑up.
o Worked your way up in a large organisation, repeatedly gaining more responsibility and influencing a large part of the codebase.
o Authored and/or maintained a popular open‑source tool or library.
o Placed in a prestigious programming competition (IOI, ICPC, etc.).
* 5+ years of professional software engineering experience.
We want to emphasize that people who feel they don’t fulfill all of these characteristics but think they would be a good fit for the position nonetheless are strongly encouraged to apply. We believe that excellent candidates can come from a variety of backgrounds and are excited to give you opportunities to shine.
Logistics
* Start Date: Target of 2–3 months after the first interview.
* Time Allocation: Full‑time.
* Location: The office is in London, next to the London Initiative for Safe AI (LISA) offices. This is an in‑person role. In rare situations, we may consider partially remote arrangements on a case‑by‑case basis.
* Work Visas: We can sponsor UK visas.
Benefits
* Salary: 100k – 200k GBP (~135k – 270k USD).
* Flexible work hours and schedule.
* Unlimited vacation.
* Unlimited sick leave.
* 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.
About the Team
The SWE team currently consists of Rusheb Shah, Andrei Matveiakin, Alex Kedrik, and Glen Rodgers. Beyond the SWE team, you will closely interact with the research scientists and engineers as the primary user group of your tools.
About The 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 detection of scheming (e.g. building evaluations), the science of scheming (e.g. model organisms), and scheming mitigations (e.g. anti‑scheming, and control). We closely work with multiple frontier AI companies, e.g. to test their models before deployment or collaborate on scheming mitigations. At Apollo, we aim for a culture that emphasizes truth‑seeking, being goal‑oriented, giving and receiving constructive feedback, and being friendly and helpful.
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.
Interview Process
Please complete the application form with your CV. The provision of a cover letter is optional but not necessary. Please also feel free to share links to relevant work samples.
About the interview process: Our multi‑stage process includes a screening interview, a take‑home test (approx. 2 hours), 3 technical interviews, and a final interview with Marius (CEO). The technical interviews will be closely related to tasks the candidate would do on the job. There are no leetcode‑style general coding interviews. If you want to prepare for the interviews, we suggest working on hands‑on LLM evals projects (e.g. as suggested in our starter guide), such as building LM agent evaluations in Inspect.
Additional Information
* Seniority level: Mid‑Senior level
* Employment type: Full‑time
* Job function: Engineering and Information Technology
* Industries: Technology, Information and Internet
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