Senior Forward Deployment Engineer - Cheminformatics & AI Modelling

AstraZeneca has invested heavily in our Augmented Design-Make-Test-Analyze IT (A-DMTA) toolsets as we seek to deliver better, differentiated candidate drugs into trials, faster, for greater patient benefit. We have made great strides in creating an ecosystem enabling operational and experimental data capture, and in developing scaled analytics, AI/ML-enabled services, and digital capabilities for both traditional small molecules and complex modalities to drive a Predict First culture in drug discovery. We are extending these capabilities with more advanced modelling, intelligent applications, and platform engineering solutions. 

We are looking for a Senior Forward Deployed Engineer with a Chemistry Background to join our team and help build our integrated software platform supporting key drug discovery science. 

In this role you will join a global team of engineers, cheminformaticians, architects, business analysts, and product managers in our Augmented Design Make Test Analyse (A-DMTA) organisation to support small molecule and new modality drug discovery as a Senior Forward Deployed Engineer.

The following will form part of the role: 

• Partner directly with scientists, product teams, and technical partners to understand high-value problems and translate them into practical engineering solutions. 

• Design, build, deploy, and improve software applications, agentic solutions, MCP servers and tools and services that support key scientific workflows in drug discovery. 

• Prototype rapidly, validate with users, and evolve successful solutions into robust, scalable, production-grade systems. 

• Bridge chemistry, cheminformatics, data, and engineering to deliver integrated solutions across scientific and technical workflows. 

• Collaborate with product, design, data science, and scientific teams to build high-impact applications and services. 

• Plan, implement, and support platform and infrastructure development with the objective of improving scalability, reliability, performance, and usability. 

• Advocate for rigorous engineering practices and discipline, including code reviews, automated testing, logging, monitoring, documentation, and maintainability. 

• Help develop and promote a strong software engineering culture across multidisciplinary teams. 

• Stay on top of relevant technology trends, experiment with new approaches, participate in internal and external technology communities, and mentor other members of the engineering community. 

• Work with modern technology stacks in cloud environments to support scientific software delivery. 

Required skills 

• Masters degree (PhD preferred) in Chemistry or a relevant field with experience in cheminformatics, chemistry toolkits, chemistry search, and related algorithms or demonstrable equivalent experience

• At least 5 years of relevant experience in the pharmaceutical industry or academia

• Strong software engineering expertise in Python, including advanced object-oriented design and development of production-quality applications and services. 

• Experience designing, building, and deploying scalable software systems, APIs, and services in production environments. 

• Strong problem-solving and solution design skills, with the ability to translate complex scientific or business needs into practical software solutions. 

• Experience working directly with users, partners, or domain experts to gather requirements, refine use cases, and deliver deployed solutions. 

• Ability to rapidly prototype solutions, validate them with users, and mature them into robust, maintainable production systems. 

• Experience integrating systems, services, and data pipelines across complex technical environments. 

• Experience with relational databases such as PostgreSQL or Oracle, and/or NoSQL technologies such as Elasticsearch. 

• Experience in data analysis, including profiling, investigating, interpreting, and documenting data structures. 

• Experience in performance tuning SQL and understanding ETL or data integration pipelines. 

• Extensive experience solving data issues, analysing end-to-end data pipelines, and improving application or service performance. 

• Good experience in consuming or exposing web APIs. 

• Experience designing, developing, and deploying production-grade scalable applications using container technologies like Docker and Kubernetes. 

• Production experience delivering CI/CD pipelines using tools such as GitHub Actions, ArgoCD, or similar. 

• Experience creating and evaluating engineering architecture in the cloud. 

• Excellent verbal and written communication skills for effective collaboration with engineers, testers, architects, product managers, scientists, and other partners. 

• Ability to work effectively in fast-moving and ambiguous environments, with ownership of delivery from problem definition through deployment and iteration. 

The following skills would be advantageous for your application but are not considered essential: 

• Experience working with AWS. 

• DevOps experience, including deployment workflows and monitoring tools such as Grafana, Prometheus, and GitHub Actions. 

• Working knowledge of Scrum or Agile delivery. 

• Product ownership or technical leadership experience, with strong partner communication and management. 

• Exposure to AI/ML-enabled applications in production, particularly where these are embedded within broader scientific or engineering platforms. 

• Development of agentic systems, MCP servers or tools