Software Engineer (Full-Stack)
AstraZeneca View all jobs
- Jing'an, Shanghai
- Permanent
- Full-time
- Lead end-to-end delivery of AI-driven platforms—designing agent orchestration, MLOps, secure web interfaces, APIs, and scalable data/service layers for functional agents.
- Design scalable service architectures (microservices or modular monoliths), implement REST/GraphQL APIs, and integrate model inference services and prompt orchestration layers.
- Build intuitive UIs for authoring prompts, reviewing generated code, lineage tracking, and approvals, with strong auditability and role-based access control.
- Implement data pipelines for metadata (e.g., CDISC standards, controlled terminology) and connect to code repositories, compute backends, and execution sandboxes.
- Establish engineering best practices: code quality, unit/integration tests, CI/CD, containerization, infrastructure-as-code, observability, and automated security checks.
- Ensure compliance and security by design: authentication, authorization, encryption, secrets management, logging, and traceability aligned with GxP expectations where applicable.
- Collaborate on product discovery, translate user needs into technical designs, estimate and prioritize work, and deliver iterative releases.
- Support production systems (monitoring, incident response, root cause analysis) and drive continuous improvement in performance and reliability.
- Bachelor’s degree or above in Computer Science, Software Engineering, or related field, or equivalent practical experience.
- 3–5 years of professional full‑stack development experience delivering production web applications and APIs.
- Proficiency in at least one modern front‑end framework (e.g., React, Vue, or Angular) and TypeScript; strong UX fundamentals for data-heavy workflows.
- Proficiency in back‑end development with one or more languages (e.g., Python, Node.js/TypeScript, or Java/Kotlin) and web frameworks (e.g., FastAPI, Express, Spring Boot).
- Experience designing and consuming REST and/or GraphQL APIs; familiarity with asynchronous processing (e.g., Celery, RabbitMQ, Kafka, or cloud-native queues).
- Strong experience with relational databases (e.g., PostgreSQL) and ORMs; comfort with schema design, migrations, and query optimization.
- Hands-on experience with containerization (Docker) and CI/CD pipelines; deploying to cloud or on‑prem Kubernetes or serverless environments.
- Solid understanding of authentication/authorization (OAuth2/OIDC), secrets management, and implementing audit logs and role-based access control.
- Excellent collaboration and communication skills with cross‑functional teams.
- Familiarity with AI application patterns (prompt orchestration, evaluation, retrieval-augmented generation) and integrating model inference services.
- Experience building code review or code execution platforms (e.g., sandboxes, notebooks, or automated linters/test runners).
- Experience with data lineage, provenance, and compliance reporting features.
- Observability stack experience (e.g., OpenTelemetry, Prometheus, Grafana, ELK) and secure software development lifecycle practices (SAST/DAST).
- Experience with domain-driven design and event-driven architectures.
- Exposure to clinical data standards (CDISC SDTM, ADaM) or regulated software delivery (GxP, CSV) in life sciences.