Flagship Pioneering
Cambridge, Cambridgeshire
Quotient Therapeutics is a privately held, early stage company developing breakthrough medicines informed by natural somatic genetic diversity present in patients. Through our work in somatic genomics, we are forging a new standard for biopharma research and development across a broad pipeline of internal and partnered programs. Position Summary We are seeking a mid level Platform Engineer to help build, operate, and improve the cloud infrastructure that underpins our genomics first drug discovery platform. This varied and challenging role is suited to someone with solid cloud and DevOps foundations who enjoys solving real world problems and continuously improving systems. Working within the Data Infrastructure team, you will collaborate closely with biologists, informaticians, and software engineers to support data pipelines, applications, and AI/ML workflows used across the company. You will take ownership of meaningful parts of the platform while continuing to grow your skills across cloud architecture, security, and data intensive systems. This role offers exposure to complex scientific workloads and the opportunity to shape how a modern biotech platform is built. This role is based at the Chesterford Research Campus (vicinity of Cambridge) and reports to the Head of Data Engineering. Applicants require permission to work in the UK. Key Responsibilities Operate and improve our AWS based platform across development and production environments. Build and maintain infrastructure as code (primarily CDK) for provisioning and managing cloud resources. Contribute to CI/CD pipelines and automation used across engineering teams. Support and optimise use of AWS services such as EC2, S3, Lambda, Batch, ECS/EKS, and RDS. Improve observability through logging, monitoring, alerting, and cost visibility. Troubleshoot issues across infrastructure, pipelines, and applications. Collaborate with non cloud experts to understand requirements and translate them into practical solutions. Contribute to improving security practices (IAM, access control, auditing) and overall platform reliability. Requirements 2-5 years of experience working with AWS cloud infrastructure. Experience writing code or scripts (Python, Bash, or similar) in a production or project setting. Hands on experience with infrastructure as code (CDK, Terraform, or CloudFormation). Experience with CI/CD pipelines, containerisation, and modern software engineering practices. Working knowledge of core cloud services (compute, storage, networking, IAM). Experience troubleshooting and improving production systems. Strong problem solving skills and ability to work through unfamiliar challenges. Good communication skills and ability to work with engineers, scientists, and other stakeholders. Familiarity with observability tooling (CloudWatch, Grafana), cloud security best practices, managing large datasets, data pipelines or data engineering workflows, and scientific/imaging/analytical workloads. Exposure to genomics or biology data is a plus. Equal Opportunity Employer We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
Quotient Therapeutics is a privately held, early stage company developing breakthrough medicines informed by natural somatic genetic diversity present in patients. Through our work in somatic genomics, we are forging a new standard for biopharma research and development across a broad pipeline of internal and partnered programs. Position Summary We are seeking a mid level Platform Engineer to help build, operate, and improve the cloud infrastructure that underpins our genomics first drug discovery platform. This varied and challenging role is suited to someone with solid cloud and DevOps foundations who enjoys solving real world problems and continuously improving systems. Working within the Data Infrastructure team, you will collaborate closely with biologists, informaticians, and software engineers to support data pipelines, applications, and AI/ML workflows used across the company. You will take ownership of meaningful parts of the platform while continuing to grow your skills across cloud architecture, security, and data intensive systems. This role offers exposure to complex scientific workloads and the opportunity to shape how a modern biotech platform is built. This role is based at the Chesterford Research Campus (vicinity of Cambridge) and reports to the Head of Data Engineering. Applicants require permission to work in the UK. Key Responsibilities Operate and improve our AWS based platform across development and production environments. Build and maintain infrastructure as code (primarily CDK) for provisioning and managing cloud resources. Contribute to CI/CD pipelines and automation used across engineering teams. Support and optimise use of AWS services such as EC2, S3, Lambda, Batch, ECS/EKS, and RDS. Improve observability through logging, monitoring, alerting, and cost visibility. Troubleshoot issues across infrastructure, pipelines, and applications. Collaborate with non cloud experts to understand requirements and translate them into practical solutions. Contribute to improving security practices (IAM, access control, auditing) and overall platform reliability. Requirements 2-5 years of experience working with AWS cloud infrastructure. Experience writing code or scripts (Python, Bash, or similar) in a production or project setting. Hands on experience with infrastructure as code (CDK, Terraform, or CloudFormation). Experience with CI/CD pipelines, containerisation, and modern software engineering practices. Working knowledge of core cloud services (compute, storage, networking, IAM). Experience troubleshooting and improving production systems. Strong problem solving skills and ability to work through unfamiliar challenges. Good communication skills and ability to work with engineers, scientists, and other stakeholders. Familiarity with observability tooling (CloudWatch, Grafana), cloud security best practices, managing large datasets, data pipelines or data engineering workflows, and scientific/imaging/analytical workloads. Exposure to genomics or biology data is a plus. Equal Opportunity Employer We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.