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CSL

Develops and delivers biotherapies and vaccines

Associate Director - AI Engineering

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in a physical, life, or quantitative science or in engineering, or equivalent experience, is required; an advanced degree is preferred.
  • At least 10 years of experience building and operating production software, with a substantial share as a hands-on architect or principal-level engineer who thinks in systems.
  • Experience building or operating software in regulated, validated environments, such as GxP, computer system validation, IQ/OQ/PQ, or requirements traceability.
  • Demonstrated, sustained daily use of agentic development tools such as Claude Code or Codex to design, build, and ship software, with full ownership of generated code evidenced by delivered professional or personal software.
  • Experience owning continuous integration and continuous delivery, infrastructure as code, and release engineering with a globally distributed team, including pipelines, environments, deployment and rollback, and observability.
  • A track record of taking inherited or prototype code to production grade through refactoring, test coverage, security hardening, performance, and operability.
  • Experience solving production concerns between applications and platforms, such as authentication and single sign-on, secrets, networking, and access control, and turning them into reusable patterns.
  • Fluency in at least one production programming language and the judgment to direct agents across a polyglot stack; the team's stack includes Python, TypeScript, and PostgreSQL.
  • Deep cloud-native experience, including containers and serverless, workflow orchestration, identity and access management and least-privilege design, and managed data stores. AWS is preferred; equivalent Azure or Google Cloud Platform depth is considered.

Responsibilities

  • Own engineering standards and production readiness for every application the team ships. Select and maintain the team's standard languages, frameworks, and supported versions based on security, maintainability, enterprise compatibility, and what AI-assisted development builds most reliably. Make architecture, release, and incident-response decisions without escalation within agreed governance, security, and quality requirements.
  • Take prototypes built by scientists and colleagues with agentic tools to production grade by refactoring, strengthening, and productizing them with sound architecture, tests, observability, security, documentation, and operability. Assess prototypes against agreed engineering standards and work with stakeholders to recommend and implement retain, rebuild, or retire decisions.
  • Own application-to-platform integration, including recurring production concerns such as authentication and single sign-on, secrets, networking, deployment, and monitoring. Solve these concerns for the team, build them into reusable patterns, and work with the AI Platform & Enablement Associate Director and enterprise platform teams to move proven patterns into the platform.
  • Establish and maintain the team's standard development and deployment patterns, including continuous integration and delivery pipelines, infrastructure as code, environments, starter templates, monitoring, and operational runbooks for the team's applications and agents.
  • Own code-review standards and the merge gate for the team's repositories by reviewing and approving changes from scientists, colleagues, contractors, and embedded delivery engineers, none of whom report to the role. Run design and architecture reviews before applications enter shared environments, and set the review standard for AI-generated code.
  • Design and build full-stack, cloud-native systems, including APIs, orchestration and workflow services, data and vector stores, identity and access, and scientist-facing front ends, favoring managed services and simple, maintainable designs.
  • Partner with Quality and computer system validation colleagues to define and implement risk-based engineering and validation practices for large language model and agent-based applications, and build the evidence case for them. Practices may include requirements traceability, model and configuration change control, regression evaluations, controlled releases, and auditable records; Quality retains decision authority.
  • Work directly with R&D scientists and the team's scientists to define software requirements, review their code, and build engineering capability through pairing. Lead productization of the team's flagship applications, directing embedded delivery or professional-services engineers and coaching colleagues on engineering practice.
  • Gain acceptance from platform teams and Cyber for the team's deployment and access patterns. Implement application security practices in line with Cyber standards, and ensure the team's applications and delivery practice comply with the company's quality management system, security guidelines, and IT policies.
  • Own the production-support approach for the team's applications, including triage, escalation, incident follow-up, and engineering fixes, with support responsibilities agreed across the team and platform partners.
  • Bring production-readiness and risk assessments to senior leadership, with recommendations on build versus buy and which prototypes to harden or retire.

Desired Qualifications

  • Hands-on experience with large language model application patterns, including retrieval-augmented generation, vector search, and multi-stage pipelines.
  • Experience working directly with research scientists.
  • AWS cloud experience.

About the Company

CSL

Develops and delivers biotherapies and vaccines

CSL is a global biotechnology company that develops and delivers biotherapies and influenza vaccines. It focuses on plasma-derived and recombinant therapies for rare and serious diseases and sells to healthcare providers, hospitals, and governments across the Americas, Asia Pacific, and Europe. Its product range includes treatments for rare diseases, influenza vaccines, and antivenoms, produced through its R&D, manufacturing, and distribution operations. CSL differentiates itself by offering the broadest portfolio of plasma-derived and recombinant therapies and by leveraging its global footprint and emphasis on diversity to reach diverse markets. The company’s main goal is to save lives and protect health by expanding access to high-quality therapies and vaccines worldwide.

Company size
10,001+
Company stage
IPO
Headquarters
Parkville, Australia
Founded
1916

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