AstraZeneca
Website:
astrazeneca.com
Company:
https://www.linkedin.com/company/astrazeneca
Seniority: Not Applicable
Industries: Pharmaceutical Manufacturing
Job details:
Job Title: Director- Software Engineering Lead
GCL: F
Introduction To Role
Are you ready to set the technical direction for enterprise-scale AI applications that drive measurable value and improve patient outcomes? In this role, you will provide deep technical leadership for AI-powered products and platforms, guiding the responsible adoption of Generative AI and machine learning at scale! You will define the architecture, standards, and platform capabilities that multiple product teams rely on to deliver secure, reliable, and cost-efficient solutions.
Do you thrive on influencing sophisticated decisions and uniting product, data, and security collaborators to deliver AI responsibly? You will help build how we turn sophisticated information into practical insights, collaborating across the company to raise quality, accelerate delivery, and embed rigorous governance. Here, ingenuity comes with accountability—innovation is empowered, and following the accurate procedures is non-negotiable to ensure patient safety and achieve n trust.
Accountabilities
Define and lead a multi-year technical vision for AI applications and platforms, aligning technology choices to business outcomes and total cost of ownership.
Establish and carry out architecture principles, reference designs, and patterns for full-stack AI solutions (GenAI, ML, data foundations) to ensure reliability, security, and scalability.
Provide technical leadership across a portfolio of AI initiatives; review solution designs, mediate trade-offs, and ensure value delivery through stage gates and measurable objectives.
Drive shared components, APIs, model/prompt registries, feature stores, RAG services, and internal developer tooling to accelerate delivery and standardize quality.
Lead model selection frameworks, evaluation methods, prompt governance, guardrails, and human-in-the-loop patterns for LLMs, agents, and retrieval systems.
Own technical standards for SLOs, resilience, observability, and cost efficiency; guide guidelines for model and service performance monitoring and continuous improvement in production.
Embed security, privacy, and ethical AI principles into building and delivery, including bias testing, explainability, and provenance; collaborate with Security, Legal, and Compliance on governance and audits.
Translate strategy into roadmaps and reference implementations with Product, Data Science, and Platform Engineering; influence adoption through technical guidance rather than line authority.
Mentor and upskill senior engineers and technical leads; cultivate communities of practice and technical learning programs to amplify impact.
Evaluate and guide strategic technology partners and platforms (cloud, model providers, integration vendors), setting technical guardrails, SLAs, and cost controls.
Scan emerging technologies (e.g., multimodal models, agentic workflows, vector databases, privacy-preserving ML), run targeted pilots, and transition validated innovations into production-ready standards.
Essential Skills/Experience
- 15+ years in software/AI engineering with a strong record of technical leadership; experience guiding managers and senior engineers through technical influence rather than formal management.
- Bachelor’s or Master’s in Computer Science, Engineering, or related field (or equivalent experience); advanced degree preferred.
- Deep experience designing distributed, cloud-native systems and microservices; strong understanding of data architectures (OLTP/OLAP, streaming, warehousing such as Snowflake) and API ecosystems.
- Confirmed expertise with ML and GenAI solution patterns at scale, including model lifecycle management (training/fine-tuning, evaluation, drift monitoring), ML Ops, and prompt/guardrail governance.
- Proficiency across modern stacks: Python; JavaScript/TypeScript/Node.js; front-end frameworks (React/Angular/Vue); back-end (Django/Flask/Fast API); CI/CD; infrastructure-as-code; Docker/Kubernetes.
- Significant experience on AWS, Azure, or GCP for secure AI/ML deployments (handled model services, serverless, containers, GPU/accelerator usage, cost optimization).
- Hands-on familiarity with foundation models and providers (e.g., Open AI, Azure Open AI, Bedrock, Cognitive Services), RAG architectures, vector databases, and evaluation/guardrail tooling.
- Strong command of software security, privacy-by-design, and responsible AI practices; experience embedding controls into delivery processes and succeeding in audits.
- Consistent record to communicate sophisticated technical concepts to executives and non-technical collaborators; track record of cross-organizational technical influence and change leadership.
Desirable Skills/Experience
- Experience establishing internal developer platforms, reusable AI components, or model/platform Centers of Excellence.
- Background in enterprise integrations and data engineering (ETL/ELT, streaming, orchestration).
- Familiarity with analytics and visualization tools (e.g., Tableau, Power BI) as part of end-to-end product experiences.
- Exposure to regulated environments and model risk frameworks; familiarity with explain-ability and fairness tooling.
- Experience with cost modeling and Fin Ops practices for AI workloads.
When we put unexpected teams in the same room, we fuel ambitious thinking with the power to encourage life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
Why AstraZeneca
Join a place where innovation meets large-scale impact, and where unexpected teams gather to spark ambitious thinking through challenge. You will work alongside deep specialists who connect across the business to turn sophisticated data into life-changing insights, advancing our transformation into a digital and data-led enterprise. We value patience alongside ambition, empower you to spot the right opportunities, and insist on doing things the right way to protect patients and earn trust—so your technical leadership not only improves, it makes a meaningful difference in the real world.
Step into this pivotal role and shape the engineering standards that power AI at scale—apply today to build platforms and solutions that move the needle for patients and the business.
Date Posted
31-Jul-2026
Closing Date
01-Aug-2026
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
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