The ad says“Experience implementing AI-assisted engineering workflows and spec-driven development practices”
The ad says“Experience working with AWS, Kubernetes, PostgreSQL, Snowflake and modern cloud infrastructure”
The ad says“Solid software engineering background with hands-on experience in Python and modern backend development”
The ad says“Strong experience delivering distributed systems, cloud-native applications or compute-intensive platforms”
The ad says“Experience working with AWS, Kubernetes, PostgreSQL, Snowflake and modern cloud infrastructure”
The ad says“Experience working with AWS, Kubernetes, PostgreSQL, Snowflake and modern cloud infrastructure”
The ad says“Solid software engineering background with hands-on experience in Python and modern backend development”
The ad says“Experience working with AWS, Kubernetes, PostgreSQL, Snowflake and modern cloud infrastructure”
The ad says“Strong understanding of software architecture, scalability, observability and operational excellence”
The ad says“Experience with workflow orchestration systems and developer platforms”
AQEMIA brings together a diverse, multidisciplinary team of 80+ professionals based in Paris and London. Our scientists and engineers, including chemists, physicists, machine learning experts, and software engineers, work side by side to push the boundaries of early-stage drug discovery
This close collaboration across disciplines is central to our approach, enabling us to tackle complex scientific challenges from first principles and translate cutting-edge ideas into novel therapeutic candidates. At AQEMIA, team members are encouraged to contribute their expertise, learn from one another, and play an active role in shaping the future of drug invention
The Engineering team (~12 people) builds and scales the technical foundations that power Aqemia’s drug discovery engine
Bringing together expertise across software engineering, cloud infrastructure, data engineering, site reliability engineering (SRE), and scientific computing, the team designs and operates robust, secure, and high-performance platforms that enable Aqemia’s scientific and AI teams to experiment, train, deploy, and run models at scale
Their work spans data infrastructure, scientific compute systems, cloud operations, orchestration, observability, CI/CD, developer tooling, and platform scalability. By transforming cutting-edge research into reliable and scalable systems, the team accelerates the discovery of new medicines while ensuring operational excellence and an outstanding developer experience
As Engineering Manager of the Compute team, you will lead a team of 5 engineers responsible for building and evolving the compute platform that powers AQEMIA’s scientific simulations, machine learning workloads, and large-scale experimentation. You will combine strong engineering leadership with technical credibility to grow a high-performing team while delivering reliable and scalable platform capabilities
Lead, coach and develop a team of Software Engineers through regular feedback, career development and mentoring
Foster a collaborative, inclusive and high-performing engineering culture built on ownership, trust and continuous improvement
Recruit, onboard and retain exceptional engineering talent
Help engineers grow both technically and professionally while creating clear development paths
Partner with Product, Staff Engineers and Engineering Leadership to define priorities and execute the Compute roadmap
Drive predictable delivery of platform initiatives supporting scientific computing, AI workloads and internal developer platforms
Balance new capabilities, operational excellence and technical debt reduction
Identify and proactively manage delivery risks, dependencies and execution challenges
Drive high engineering standards across architecture, testing, observability, reliability and maintainability
Improve the scalability, resilience and performance of production systems supporting research and platform teams
Promote modern engineering practices including automation, CI/CD, Infrastructure as Code and AI-assisted software development
Continuously improve engineering processes, team effectiveness and operational maturity
Collaborate closely with Platform, Data, AI and Scientific teams to translate research needs into scalable engineering solutions
Facilitate communication between technical and non-technical stakeholders
Ensure engineering execution remains aligned with AQEMIA’s scientific objectives and business priorities
Support cross-functional planning, architecture discussions and technical decision-making
Partner with Engineering Leadership on organizational planning, hiring strategy and team evolution
Help define engineering standards, operating principles and best practices across the organization
Contribute to long-term platform strategy and engineering scalability
Foster knowledge sharing, technical excellence and continuous learning across teams
Preferred experience
Previous experience leading engineering teams as an Engineering Manager or Tech Lead with people management responsibilities
Solid software engineering background with hands-on experience in Python and modern backend development
Excellent communication skills with the ability to influence across engineering, scientific and business stakeholders
Strong coaching mindset with a passion for developing engineers and building high-performing teams
Experience leading roadmap execution and coordinating cross-functional engineering initiatives
8+ years of experience in Software Engineering, including experience building production systems at scale
Experience working with AWS, Kubernetes, PostgreSQL, Snowflake and modern cloud infrastructure
Strong experience delivering distributed systems, cloud-native applications or compute-intensive platforms
Strong understanding of software architecture, scalability, observability and operational excellence
Pragmatic approach to balancing delivery, technical excellence and organizational priorities
Experience with workflow orchestration systems and developer platforms
Exposure to scientific computing, machine learning infrastructure or AI platforms
Experience leading Platform Engineering, Infrastructure, Compute or SRE teams
Familiarity with large-scale compute environments, GPU infrastructure or distributed training systems
Experience implementing AI-assisted engineering workflows and spec-driven development practices
Track record of scaling engineering organizations in fast-growing technology companies
Interest in computational chemistry, life sciences or scientific research environments
Recruitment process
Talent Acquisition Interview (30 min)
Hiring Manager Interview with Max, CEO (60 min)
Technical Assessment, with 2 members of Compute team (90 min)
Stakeholder Interview with 2 members of Engineering department (60 min)
VP Interview with Nicolas, VP Platform (60 min)
Culture Fit Interview with Emmanuelle, Co-founder & COO (45 min)
