AI Security Institute
Misuse Red Team - Research Engineer/Research Scientist London, UK About the AI Security Institute The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We're in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally. We're here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action. The deadline for applying to this role is 30 th September 2026 , end of day, anywhere on Earth. Team Description Interventions that secure a system from abuse by bad actors or misaligned AI systems will grow in importance as AI systems become more capable, autonomous, and integrated into society. The Misuse Red Team is a specialised subteam within AISI's wider Red Team. W e red - team frontier AI safeguards for dangerous capabilities , research novel attack vectors , and develop advanced automated attack tooling . We share our findings with frontier AI companies (including Anthropic , OpenAI , DeepMind ) , key UK officials, and other governments to inform their respective deployment, research, and policy decision-making . We're looking for research scientists and research engineers for our misuse sub-team with expertise developing and analysing attacks and protections for systems based on large language models or who have broader experience with frontier LLM research and development. An ideal candidate would have a strong track record of performing and publishing novel and impactful research in these or other areas of LLM research. We're looking for: Research Scientists , who typically lead technical direction -pickingthe questions, designingthe experiments, and owningthe conclusions (typicallyevidencedby a strong publication record). Research Engineers , who typically lead execution - building the systems and code that make thoseexperimentspossible at scale, and owningreliability, speed, and reproducibility. In practice, wecan support staff's work spanning or alternating between research and engineering. If you have a preference, please specify this in your application. The team is currently led by Eric Winsor and Xander Davies . You'll work with incredible technical staff across AISI, including alumni from Anthropic, OpenAI, DeepMind, and top universities. You may also collaborate with external teams from Anthropic, OpenAI, and Gray Swan. We are open to hires at junior, senior, staff and principal research scientist levels. Representative projects you might work on Designing, building,runningand evaluating methods to automatically attack and evaluate safeguards, such as LLM-automated attacking and direct optimisation approaches. Building a benchmark for asynchronous monitoring for signs of misuse and jailbreak development across multiple model interactions. Investigating novel attacks and defences for data poisoning LLMs with backdoors or other attacker goals. Performing adversarial testing of frontier AI system safeguards and producingreports that are impactful and action-guiding for safeguard developers. What we're looking for The experiences listed below should be interpreted as examples of the expertise we're looking for, as opposed to a list of everything we expect to find in one applicant: You may be a good fit if you have: Hands-on research experience with large language models (LLMs) - such as training, fine-tuning, evaluation, or safety research. A demonstratedtrack recordof peer-reviewed publications in top-tier ML conferences or journals. Ability and experience writing clean, documented research code for machine learning experiments, including experience with ML frameworks likePyTorchor evaluation frameworks like Inspect. A sense of mission, urgency, responsibility for success. An ability to bring your own research ideas and work in a self-directed way, while also collaborating effectively and prioritizing team efforts over extensive solo work. Strong candidates may also have: Experience working on adversarial robustness, other areas of AI security, or red teaming against any kind of system. Experience working on AI alignment or AI control. Extensive experience writing production quality code. Desire to and experience with improving our team through mentoring and feedback. Experience designing, shipping, and maintaining complex technical products. Selection process The interview process may vary candidate tocandidate,however, you should expect a typical process to include some technicalproficiencytests, discussions with a cross-section of our team at AISI (including non-technical staff), conversations with your team lead. The process will culminate in a conversation with members of the senior leadership team here at AISI. Candidates should expect to go through some orall ofthe following stages once an application has beensubmitted: Initial assessment Initial screening call Research interview Technical assessment Behavioural interview Final interview with members of the senior leadership team What We Offer Impactyoucouldn'thave anywhere else Incredibly talented, mission-drivenand supportive colleagues. Direct influence on how frontier AI is governed and deployed globally. Work with the Prime Minister's AI Advisor and leading AI companies. Opportunity to shape the first & best-resourced public-interest research team focused on AI security. Resources & access Pre-release access to multiple frontier models and ample compute. Extensive operational support so you can focus on research and ship quickly. Work with experts across national security, policy, AI researchand adjacent sciences. Ifyou'retalented and driven,you'llown important problems early. 5 days offand annual stipends forlearning and development, andfunding for conferences and external collaborations. Freedom to pursue research bets without product pressure. Opportunities to publish and collaborate externally. Life & family Modern central London office, or where applicable, option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol. Hybrid working, flexibility for occasional remote work abroad and stipends for work-from-home equipment. At least 25 days' annual leave, 8 public holidays, extra team-widebreaksand 3 days off for volunteering. Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option foradditionalunpaid time). On top of your salary, we contribute 28.97% of your base salary to your pension. Discounts and benefits for cycling to work, donations and retail/gyms. Annual salary is benchmarked to role scope and relevant experience. Most offers land between £65,000 and £145,000 made up of a base salary plus a technical allowance (take-home salary = base + technical allowance). An additional 28.97% employer pension contribution is paid on the base salary. This role sits outside of the DDaT pay framework given the scope of this role requires in depth technicalexpertisein frontier AI safety,robustnessand advanced AI architectures. The full range of salaries are available below: Additional Information Use of AI in Applications Artificial Intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see candidate guidance for more information on appropriate and inappropriate use.
Misuse Red Team - Research Engineer/Research Scientist London, UK About the AI Security Institute The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We're in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally. We're here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action. The deadline for applying to this role is 30 th September 2026 , end of day, anywhere on Earth. Team Description Interventions that secure a system from abuse by bad actors or misaligned AI systems will grow in importance as AI systems become more capable, autonomous, and integrated into society. The Misuse Red Team is a specialised subteam within AISI's wider Red Team. W e red - team frontier AI safeguards for dangerous capabilities , research novel attack vectors , and develop advanced automated attack tooling . We share our findings with frontier AI companies (including Anthropic , OpenAI , DeepMind ) , key UK officials, and other governments to inform their respective deployment, research, and policy decision-making . We're looking for research scientists and research engineers for our misuse sub-team with expertise developing and analysing attacks and protections for systems based on large language models or who have broader experience with frontier LLM research and development. An ideal candidate would have a strong track record of performing and publishing novel and impactful research in these or other areas of LLM research. We're looking for: Research Scientists , who typically lead technical direction -pickingthe questions, designingthe experiments, and owningthe conclusions (typicallyevidencedby a strong publication record). Research Engineers , who typically lead execution - building the systems and code that make thoseexperimentspossible at scale, and owningreliability, speed, and reproducibility. In practice, wecan support staff's work spanning or alternating between research and engineering. If you have a preference, please specify this in your application. The team is currently led by Eric Winsor and Xander Davies . You'll work with incredible technical staff across AISI, including alumni from Anthropic, OpenAI, DeepMind, and top universities. You may also collaborate with external teams from Anthropic, OpenAI, and Gray Swan. We are open to hires at junior, senior, staff and principal research scientist levels. Representative projects you might work on Designing, building,runningand evaluating methods to automatically attack and evaluate safeguards, such as LLM-automated attacking and direct optimisation approaches. Building a benchmark for asynchronous monitoring for signs of misuse and jailbreak development across multiple model interactions. Investigating novel attacks and defences for data poisoning LLMs with backdoors or other attacker goals. Performing adversarial testing of frontier AI system safeguards and producingreports that are impactful and action-guiding for safeguard developers. What we're looking for The experiences listed below should be interpreted as examples of the expertise we're looking for, as opposed to a list of everything we expect to find in one applicant: You may be a good fit if you have: Hands-on research experience with large language models (LLMs) - such as training, fine-tuning, evaluation, or safety research. A demonstratedtrack recordof peer-reviewed publications in top-tier ML conferences or journals. Ability and experience writing clean, documented research code for machine learning experiments, including experience with ML frameworks likePyTorchor evaluation frameworks like Inspect. A sense of mission, urgency, responsibility for success. An ability to bring your own research ideas and work in a self-directed way, while also collaborating effectively and prioritizing team efforts over extensive solo work. Strong candidates may also have: Experience working on adversarial robustness, other areas of AI security, or red teaming against any kind of system. Experience working on AI alignment or AI control. Extensive experience writing production quality code. Desire to and experience with improving our team through mentoring and feedback. Experience designing, shipping, and maintaining complex technical products. Selection process The interview process may vary candidate tocandidate,however, you should expect a typical process to include some technicalproficiencytests, discussions with a cross-section of our team at AISI (including non-technical staff), conversations with your team lead. The process will culminate in a conversation with members of the senior leadership team here at AISI. Candidates should expect to go through some orall ofthe following stages once an application has beensubmitted: Initial assessment Initial screening call Research interview Technical assessment Behavioural interview Final interview with members of the senior leadership team What We Offer Impactyoucouldn'thave anywhere else Incredibly talented, mission-drivenand supportive colleagues. Direct influence on how frontier AI is governed and deployed globally. Work with the Prime Minister's AI Advisor and leading AI companies. Opportunity to shape the first & best-resourced public-interest research team focused on AI security. Resources & access Pre-release access to multiple frontier models and ample compute. Extensive operational support so you can focus on research and ship quickly. Work with experts across national security, policy, AI researchand adjacent sciences. Ifyou'retalented and driven,you'llown important problems early. 5 days offand annual stipends forlearning and development, andfunding for conferences and external collaborations. Freedom to pursue research bets without product pressure. Opportunities to publish and collaborate externally. Life & family Modern central London office, or where applicable, option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol. Hybrid working, flexibility for occasional remote work abroad and stipends for work-from-home equipment. At least 25 days' annual leave, 8 public holidays, extra team-widebreaksand 3 days off for volunteering. Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option foradditionalunpaid time). On top of your salary, we contribute 28.97% of your base salary to your pension. Discounts and benefits for cycling to work, donations and retail/gyms. Annual salary is benchmarked to role scope and relevant experience. Most offers land between £65,000 and £145,000 made up of a base salary plus a technical allowance (take-home salary = base + technical allowance). An additional 28.97% employer pension contribution is paid on the base salary. This role sits outside of the DDaT pay framework given the scope of this role requires in depth technicalexpertisein frontier AI safety,robustnessand advanced AI architectures. The full range of salaries are available below: Additional Information Use of AI in Applications Artificial Intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see candidate guidance for more information on appropriate and inappropriate use.
AI Security Institute
Control Red Team - Research Engineer/Research Scientist London, UK About the AI Security Institute The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We're in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally. We're here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action. The deadline for applying to this role is 30 th September 2026 , end of day, anywhere on Earth. Team Description Control measures - monitors, permission systems, sandboxing, resampling, escalation protocols - are designed to detect and prevent misaligned behaviour from advanced AI systems. Though the measures are already critical to safety, whether they would in fact catch a capable model attempting to cause harm is an empirical question that remains largely untested. We're opening roles on the Control Red Team, and we think it's an unusually good place to do this work. You'd join early, with real ownership over the team's direction; you'd have frontier model access, serious compute and strong infrastructure support from across AISI; and you'd get privileged insight into control measures across several frontier developers, working alongside some of the most experienced red teamers in the field. Our current bet is to focus our effort on monitoring : the measures frontier companies lean on most heavily, and the ones where the science of evaluation is not yet settled. About the Role What You'll Be Doing You'll spend your time across two tracks of work: 1. Research: How and what should we measure to understand the efficacy of control measures? How can we gather empirical evidence about how likely a monitor is to prevent harm - and what can we legitimately conclude from it? How do you estimate a monitor's recall against dangerous behaviours nobody has seen yet? These are difficult questions - conceptually and empirically. Day to day this looks like: designing and running ML experiments (including RL and other optimisation-heavy work), building the adversarial attacks that generate the evidence, writing arguments, and arguing them out with the rest of the team. We intend to publish this work. 2. Testing: Running evaluations of frontier labs' monitors, and reporting the implications . Turning our research into concrete assessments of real systems: threat modelling how an AI attacker would actually operate in a frontier internal deployment; breaking monitors, sandboxes and the surrounding infrastructure; conducting security analyses; and producing reports that are decision-relevant and action-guiding for the companies and for government. Underpinning both: Building tooling and experimental pipelines that let us go from question to result fast, at a quality bar that makes the results reusable. Heavy use of LLMs to automate our own attack, evaluation and analysis loops - and getting faster as models improve. Building and running the infrastructure for training and serving models at the scale our experiments need. Research Scientists and Research Engineers We're looking for research science and engineering skills, and we're excited to hear from strong scientists, strong engineers, and people who are a bit of both. We're deliberately open on seniority. For exceptional candidates, with experience leading research teams, we'll grow the scope to match. What We're Looking For The experiences listed are examples of the expertise we're looking for, rather than a list of everything we expect to find in one applicant. Demonstrated ability to design, build and run ML experiments on frontier models, and to work autonomously on complex research projects involving substantial engineering. This includes black-box work (API-based evaluations and attacks) and ideally some white-box work (e.g. fine-tuning open-weight models). Strong software engineering and ML experience: writing clean, documented, reusable code for machine learning experiments - beyond one-off research scripts - including experience with LLM finetuning and inference frameworks , or evaluation frameworks like Inspect. The ability to understand and critique how an experiment does and does not support a safety claim - including an understanding of why AI safety and control are hard problems, or a clear appetite to get up to speed fast. Impact-driven mindset and a collaborative team player: motivated by the work that most reduces risk rather than what is superficially impressive, flexibly about what needs doing, and high velocity with a high-quality bar for outputs. Highly Desirable We don't expect candidates to have all of these - they're additional signals that help us identify exceptional fits for specific aspects of the role. A good working model of frontier AI companies' internal deployments: what their ML infrastructure and dev practices look like, the kinds of experiments they run internally, and where the security weak points and easiest escape routes would be. An exceptional red teaming mindset - instinctively finding the path a capable adversary would actually take , whether against a model, a monitor or a sandbox. Experience with ML optimisation: RL, SFT, evolutionary methods, or similar. Experience optimising hard against a defined metric and making (and justifying) careful measurement choices. Strong written communication and argumentation: high-quality research write ups in any medium - a paper, a blog post, an internal report, an unusually good thread - where the reasoning, not just the result, is the point. Willingness and ability to construct and defend arguments for safety claims, and to think about which claims are worth making in the first place. Experience building or operating ML research infrastructure at a large organisation: GPU management, running experiments at scale, securing evaluation environments. Experience in cybersecurity or security analysis, including attacking LLM based applications and agent scaffolds. Familiarity with the AI control and adversarial ML literature, and existing relationships with researchers working on control at labs or in the wider safety community. Participation in an AI safety research or fellowship programme, or equivalent evidence of independent research output. Broad evidence of strong mathematical, scientific or analytic ability (for example, highly competitive courses or programmes, or olympiad -level results. Proficient use of LLM coding tools and agents. We are less interested in credentials as such: a first-author conference paper or a CS degree is welcome evidence, but neither is required , and neither substitutes for the signals above. Selection process The interview process may vary from candidate to candidate; however, you should expect a typical process to include some technical proficiency tests, discussions with a cross-section of our team at AISI (including non-technical staff), and conversations with your team lead. The process will culminate in a conversation with members of the senior leadership team here at AISI. Candidates should expect to go through some or all of the following stages once an application has been submitted: Initial assessment Initial screening call Technical assessment Behavioural interview Research interview Final interview with members of the senior leadership team What We Offer Impactyoucouldn'thave anywhere else Incredibly talented, mission-drivenand supportive colleagues. Direct influence on how frontier AI is governed and deployed globally. Work with the Prime Minister's AI Advisor and leading AI companies. Opportunity to shape the first & best-resourced public-interest research team focused on AI security. Resources & access Pre-release access to multiple frontier models and ample compute. Extensive operational support so you can focus on research and ship quickly. Work with experts across national security, policy, AIresearchand adjacent sciences. Ifyou'retalented and driven,you'llown important problems early. 5 days offand annual stipends forlearning and development, andfunding for conferences and external collaborations. Freedom to pursue research bets without product pressure. Opportunities to publish and collaborate externally. Life & family Modern central London office, or where applicable, option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol. Hybrid working, flexibility for occasional remote work abroad and stipends for work-from-home equipment. At least 25 days' annual leave, 8 public holidays, extra team-widebreaksand 3 days off for volunteering. Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option foradditionalunpaid time). On top of your salary, we contribute 28.97% of your base salary to your pension. Discounts and benefits for cycling to work, donations and retail/gyms. These benefits apply to direct employees . click apply for full job details
Control Red Team - Research Engineer/Research Scientist London, UK About the AI Security Institute The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We're in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally. We're here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action. The deadline for applying to this role is 30 th September 2026 , end of day, anywhere on Earth. Team Description Control measures - monitors, permission systems, sandboxing, resampling, escalation protocols - are designed to detect and prevent misaligned behaviour from advanced AI systems. Though the measures are already critical to safety, whether they would in fact catch a capable model attempting to cause harm is an empirical question that remains largely untested. We're opening roles on the Control Red Team, and we think it's an unusually good place to do this work. You'd join early, with real ownership over the team's direction; you'd have frontier model access, serious compute and strong infrastructure support from across AISI; and you'd get privileged insight into control measures across several frontier developers, working alongside some of the most experienced red teamers in the field. Our current bet is to focus our effort on monitoring : the measures frontier companies lean on most heavily, and the ones where the science of evaluation is not yet settled. About the Role What You'll Be Doing You'll spend your time across two tracks of work: 1. Research: How and what should we measure to understand the efficacy of control measures? How can we gather empirical evidence about how likely a monitor is to prevent harm - and what can we legitimately conclude from it? How do you estimate a monitor's recall against dangerous behaviours nobody has seen yet? These are difficult questions - conceptually and empirically. Day to day this looks like: designing and running ML experiments (including RL and other optimisation-heavy work), building the adversarial attacks that generate the evidence, writing arguments, and arguing them out with the rest of the team. We intend to publish this work. 2. Testing: Running evaluations of frontier labs' monitors, and reporting the implications . Turning our research into concrete assessments of real systems: threat modelling how an AI attacker would actually operate in a frontier internal deployment; breaking monitors, sandboxes and the surrounding infrastructure; conducting security analyses; and producing reports that are decision-relevant and action-guiding for the companies and for government. Underpinning both: Building tooling and experimental pipelines that let us go from question to result fast, at a quality bar that makes the results reusable. Heavy use of LLMs to automate our own attack, evaluation and analysis loops - and getting faster as models improve. Building and running the infrastructure for training and serving models at the scale our experiments need. Research Scientists and Research Engineers We're looking for research science and engineering skills, and we're excited to hear from strong scientists, strong engineers, and people who are a bit of both. We're deliberately open on seniority. For exceptional candidates, with experience leading research teams, we'll grow the scope to match. What We're Looking For The experiences listed are examples of the expertise we're looking for, rather than a list of everything we expect to find in one applicant. Demonstrated ability to design, build and run ML experiments on frontier models, and to work autonomously on complex research projects involving substantial engineering. This includes black-box work (API-based evaluations and attacks) and ideally some white-box work (e.g. fine-tuning open-weight models). Strong software engineering and ML experience: writing clean, documented, reusable code for machine learning experiments - beyond one-off research scripts - including experience with LLM finetuning and inference frameworks , or evaluation frameworks like Inspect. The ability to understand and critique how an experiment does and does not support a safety claim - including an understanding of why AI safety and control are hard problems, or a clear appetite to get up to speed fast. Impact-driven mindset and a collaborative team player: motivated by the work that most reduces risk rather than what is superficially impressive, flexibly about what needs doing, and high velocity with a high-quality bar for outputs. Highly Desirable We don't expect candidates to have all of these - they're additional signals that help us identify exceptional fits for specific aspects of the role. A good working model of frontier AI companies' internal deployments: what their ML infrastructure and dev practices look like, the kinds of experiments they run internally, and where the security weak points and easiest escape routes would be. An exceptional red teaming mindset - instinctively finding the path a capable adversary would actually take , whether against a model, a monitor or a sandbox. Experience with ML optimisation: RL, SFT, evolutionary methods, or similar. Experience optimising hard against a defined metric and making (and justifying) careful measurement choices. Strong written communication and argumentation: high-quality research write ups in any medium - a paper, a blog post, an internal report, an unusually good thread - where the reasoning, not just the result, is the point. Willingness and ability to construct and defend arguments for safety claims, and to think about which claims are worth making in the first place. Experience building or operating ML research infrastructure at a large organisation: GPU management, running experiments at scale, securing evaluation environments. Experience in cybersecurity or security analysis, including attacking LLM based applications and agent scaffolds. Familiarity with the AI control and adversarial ML literature, and existing relationships with researchers working on control at labs or in the wider safety community. Participation in an AI safety research or fellowship programme, or equivalent evidence of independent research output. Broad evidence of strong mathematical, scientific or analytic ability (for example, highly competitive courses or programmes, or olympiad -level results. Proficient use of LLM coding tools and agents. We are less interested in credentials as such: a first-author conference paper or a CS degree is welcome evidence, but neither is required , and neither substitutes for the signals above. Selection process The interview process may vary from candidate to candidate; however, you should expect a typical process to include some technical proficiency tests, discussions with a cross-section of our team at AISI (including non-technical staff), and conversations with your team lead. The process will culminate in a conversation with members of the senior leadership team here at AISI. Candidates should expect to go through some or all of the following stages once an application has been submitted: Initial assessment Initial screening call Technical assessment Behavioural interview Research interview Final interview with members of the senior leadership team What We Offer Impactyoucouldn'thave anywhere else Incredibly talented, mission-drivenand supportive colleagues. Direct influence on how frontier AI is governed and deployed globally. Work with the Prime Minister's AI Advisor and leading AI companies. Opportunity to shape the first & best-resourced public-interest research team focused on AI security. Resources & access Pre-release access to multiple frontier models and ample compute. Extensive operational support so you can focus on research and ship quickly. Work with experts across national security, policy, AIresearchand adjacent sciences. Ifyou'retalented and driven,you'llown important problems early. 5 days offand annual stipends forlearning and development, andfunding for conferences and external collaborations. Freedom to pursue research bets without product pressure. Opportunities to publish and collaborate externally. Life & family Modern central London office, or where applicable, option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol. Hybrid working, flexibility for occasional remote work abroad and stipends for work-from-home equipment. At least 25 days' annual leave, 8 public holidays, extra team-widebreaksand 3 days off for volunteering. Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option foradditionalunpaid time). On top of your salary, we contribute 28.97% of your base salary to your pension. Discounts and benefits for cycling to work, donations and retail/gyms. These benefits apply to direct employees . click apply for full job details