Senior Data Infrastructure Engineer - Cloud & AI Platform

Quotient Therapeutics; Cambridge; Hybrid; GBP 120,000 - 160,000; Full time

Job summary

Quotient Therapeutics in Cambridge is seeking a Senior Engineer for the Data Infrastructure team to design and evolve our AWS-based cloud, data and AI infrastructure underpinning our genomics-first drug discovery platform.

You will lead cross-functional initiatives across AWS platform engineering, data systems and AI/ML workloads, mentoring Cloud and Data Engineers and translating scientific needs into secure, reliable platform capabilities.

Qualifications

• Seven+ years of experience designing, building and operating production cloud/data infrastructure.
• Advanced hands-on experience with AWS and multi-system ownership.
• Infrastructure-as-code, CI/CD, containerised workloads and production observability.

Responsibilities

• Lead architecture and evolution of AWS-based infrastructure across cloud services, data platforms and AI/ML workloads.
• Design reusable infrastructure-as-code, CI/CD and environment-management patterns.
• Own cross-cutting decisions for observability, IAM, networking, resilience and data lifecycle management.
• Mentor Cloud and Data Engineers through design reviews, delivery and troubleshooting.
• Translate scientific data needs into secure, reproducible platform capabilities with AI/ML teams.
• Diagnose complex failures spanning infra, data pipelines and AI workloads; drive incident reviews and improvements.
• Set engineering standards for testing, release readiness, security and cost visibility.

Skills

Mentoring engineers

Cross-functional collaboration

Python

Linux

Observability

Security best practices

Tools

AWS

AWS CDK

Batch

ECS

EKS

S3

RDS/Postgres

Athena

SageMaker

Bedrock

Job description

Quotient Therapeutics in Cambridge is seeking a Senior Engineer for the Data Infrastructure team to design and evolve our AWS-based cloud, data and AI infrastructure underpinning our genomics-first drug discovery platform.

You will lead cross-functional initiatives across AWS platform engineering, data systems and AI/ML workloads, mentoring Cloud and Data Engineers and translating scientific needs into secure, reliable platform capabilities.