
Associate Director, AI Engineering
Waltham, MAJobSeen todaySeen in employer's feed today
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Job overview
The Associate Director is the team’s senior full-stack engineer and architect, responsible for turning scientist-built prototypes into robust, tested, supportable, validation-ready production systems. This hands-on individual-contributor role sets engineering standards and production patterns, builds and reviews software, and partners with R&D scientists, Quality, Cyber, and platform teams. It also leads productization, production support, and risk-based engineering practices for the team’s applications.
Skills & qualifications
Skills
Qualifications
Full job description
Deliver robust, tested and supportable systems from the team's working prototypes to R&D scientists. The Associate Director is the team's senior full-stack engineer and architect. The role owns the engineering standards, development and deployment patterns, and production readiness for every application the team ships, and decides how software built with agentic tools by scientists and colleagues becomes durable, validation-ready systems. Its decisions set how quickly prototypes become products, how reliable those products are, and whether they are ready for validation. The role partners with a peer Associate Director, AI Platform & Enablement, who turns proven team patterns into shared platform capabilities over time. This is a hands-on individual-contributor role: the Associate Director designs, builds, debugs and reviews production software, working in agentic development tools (e.g., Claude Code, Codex) throughout the day, alongside validated-system work that follows its own procedures.
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: refactor, strengthen and productize 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: the production concerns that recur across applications, such as authentication and single sign-on, secrets, networking, deployment and monitoring. Solve them for the team, build them once 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: CI/CD 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, 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: 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 LLM 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 the 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 practice 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 on which prototypes to harden or retire.
Qualifications:
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Bachelor's degree in a physical, life or quantitative science or in engineering, or equivalent experience; advanced degree preferred.
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10+ years building and operating production software, with a substantial share as a hands-on architect or principal-level engineer who thinks in systems.
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Experience building or operating software in regulated, validated environments (e.g., GxP, computer system validation, IQ/OQ/PQ, requirements traceability) required.
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Demonstrated, sustained daily use of agentic development tools (e.g., Claude Code, Codex) to design, build and ship software, with full ownership of generated code, evidenced by delivered software, professional or personal.
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Experience owning CI/CD, infrastructure as code and release engineering with a globally distributed team: pipelines, environments, deployment and rollback, and observability.
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Track record of taking inherited or prototype code to production grade: refactoring, test coverage, security hardening, performance and operability.
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Experience solving the production concerns that sit between applications and platforms (e.g., authentication and SSO, secrets, networking, access control) and turning them into reusable patterns.
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Fluency in at least one production language and the judgment to direct agents across a polyglot stack (the team's is Python, TypeScript and PostgreSQL).
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Deep cloud-native experience, AWS preferred (equivalent Azure or GCP depth considered): containers and serverless, workflow orchestration, IAM and least-privilege design, managed data stores.
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Hands-on LLM application patterns (RAG, vector search, multi-stage pipelines) preferred.
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Experience working directly with research scientists preferred.
About CSL Behring
CSL Behring is a global biotherapeutics leader driven by our promise to save lives. Focused on serving patients’ needs by using the latest technologies, we discover, develop and deliver innovative therapies for people living with conditions in the immunology, hematology, cardiovascular and metabolic, respiratory, and transplant therapeutic areas. We use three strategic scientific platforms of plasma fractionation, recombinant protein technology, and cell and gene therapy to support continued innovation and continually refine ways in which products can address unmet medical needs and help patients lead full lives.
CSL Behring operates one of the world’s largest plasma collection networks, CSL Plasma. Our parent company, CSL, headquartered in Melbourne, Australia, employs 32,000 people, and delivers its lifesaving therapies to people in more than 100 countries.
To learn more about CSL, CSL Behring, CSL Seqirus and CSL Vifor visit https://www.csl.com/ and CSL Plasma at https://www.cslplasma.com/ .
Our Benefits
For more information on CSL benefits visit How CSL Supports Your Well-being | CSL (https://www.cslbenefits.com/csl/candidates) .
You Belong at CSL
At CSL, Inclusion and Belonging is at the core of our mission and who we are. It fuels our innovation day in and day out. By celebrating our differences and creating a culture of curiosity and empathy, we are able to better understand and connect with our patients and donors, foster strong relationships with our stakeholders, and sustain a diverse workforce that will move our company and industry into the future.
To learn more about inclusion and belonging visit https://www.csl.com/careers/inclusion-and-belonging
Equal Opportunity Employer
CSL is an Equal Opportunity Employer. If you are an individual with a disability and need a reasonable accommodation for any part of the application process, please visit https://www.csl.com/accessibility-statement .
R-295164
CSL makes all employment decisions without regard to race, color, religion, national origin, ancestry, age, sex, gender, pregnancy, disability, marital status, sexual orientation, gender identity, genetic information, military status, protected veteran status (specifically status as a disabled veteran, recently separated veteran, armed forces service medal veteran, or active duty wartime or campaign badge veteran) or other classification protected by applicable US federal, state or local law. CSL complies with all applicable employment laws, including but not limited to Title VII of the Civil Rights Act of 1964, the Americans with Disabilities Act, the Fair Labor Standards Act, and the Immigration Reform and Control Act. https://www.cslbehring.com/careers/eeo-statement
How this job compares
Set against the 1,204 open AI Engineering jobs on Olive Jobs, counted November 7, 2026.
- Pay
- This postingNot listed
- Massachusetts median$145–252K/yr36 salary ranges
- US median$26–46/hr41 hourly ranges
- Openings
- Olive Jobs lists 41 open AI Engineering jobs in Massachusetts and 1,204 across the US. 9% of them nationwide are listed as remote or flexible.
- Hiring the most in Massachusetts
- Accenture4 open
- EY4 open
- Capital One3 open
- Experience
- This posting asks for at least 10 years of experience; AI Engineering postings that state a minimum ask for 7 years at the median (1,066 postings).
- Education
- 434 of the 1,204 open AI Engineering jobs (36%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 7, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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