Evinova - Workflow Automation and Agentic Systems Lead
AstraZeneca

Evinova delivers market-leading digital health solutions that are science-based, evidence-led and human experience-driven. Smart risks and quick decisions come together to accelerate innovation across the life sciences sector. Be part of a diverse team that pushes the boundaries of science by digitally empowering a deeper understanding of the patients we're helping. Launch game-changing digital solutions that improve the patient experience and deliver better health outcomes. Together, we have the opportunity to combine deep scientific expertise with digital and artificial intelligence to serve the wider healthcare community and create new standards across the sector.

The Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is a newly formed team of battle-tested and proven SaaS ML/AI developers and operators that will spearhead the design, creation, and operational excellence of our entire ML/AI data and computational AWS ecosystem to catalyze and accelerate science led innovations through our pharmaceutical clinical SaaS products.

This team is responsible and accountable for the design, implementation, deployment, health and performance of all algorithms, models, ML/AI operations (MLOps, AIOps, and LLMOps) and Data Science Platform. We manage ML/AI and broader cloud resources, automating operations through infrastructure-as-code and CI/CD pipelines, and ensure best-in-class operations - striving to push even beyond mere compliance with industry standards such as Good Clinical Practices (GCP) and Good Machine Learning Practice (GMLP).

On the human side of the equation, our team forges deep relationships across broader engineering, design, product and science organizations and are quitessential and consummate interdisciplinary teammates and collaborators that can build on our deep heritage within global pharmaceutical clinical trials to drive State-of-the-art (SOTA) AI product experiences with tangible and quantifiable product and business operations impact.

As the Workflow Automation and Agentic Systems Lead in our team, you will lead the design and implementation of workflow automation and agentic systems across the organization. Specializing in AWS Services (such as Sagemaker, Bedrock, Lex, OpenSearch, etc.), you will utilize the latest frameworks and methodologies in Generative AI to develop advanced automation solutions. Your expertise in prompt engineering, RAG, and LLMOps tools like DSPy, Letta, LlamaIndex, and LangChain will be pivotal in enhancing our AI capabilities and driving innovation.

This position requires a deep understanding of cloud-native ML/AI Ops methodologies and technologies, AWS infrastructure, and the unique demands of regulated industries, making it a cornerstone of our success in delivering impactful solutions to the pharmaceutical industry.

Role & Team Key Responsibilities:

Operational Excellence

• Lead by example in creating high-performance, mission-focused and interdisciplinary teams/culture founded on trust, mutual respect, growth mindsets, and an obsession for building extraordinary products with extraordinary people.
• Lead by example in using reactive firefighting to drive the creation of proactive capability and process enhancements that ensures enduring value creation and analytic compounding interest.
• Design and implement resilient cloud ML/AI operational capabilities to maximize our system A-bilities (Learnability, Flexibility, Extendibility, Interoperability, Scalability).
• Drive precision and systemic cost efficiency, optimized system performance, and risk mitigation with a data-driven strategy, comprehensive analytics, and predictive capabilities at the tree-and-forest level of our ML/AI systems, workloads and processes.

ML/AI Cloud Operations and Engineering

• Design and implement both workflow automation, and more advanced agentic systems, across the organization using AWS GenAI Services and bleeding edge agentic stacks and frameworks
• Ensure principled and methodical validation pathways and a Well Architected Framework for Embryonic Research (WAFER) similar to and building on AWS's Well Architected Framework (WAF) for all early stage GenAI PoC's across the organization.
• Maintain and teach advanced understanding of rapidly evolving frameworks such as DSPy, Letta (formerly MemGPT), LlamaIndex, LangChain, and RAG to enhance AI capabilities across engineering and science organizations.
• Apply advanced prompt engineering techniques to improve AI model interactions and outputs, and evangelize "prompts as programs" philosophy and management/governance implications.
• Embed deeply within and across product, design, science and business teams to identify, scope and integrate workflow automation and agentic systems that have tangible and quantifiable product and business impact.

Personal Attributes:

• Customer-obsessed and passionate about building products that solve real-world problems.
• Highly organized and detail-oriented, with the ability to manage multiple initiatives and deadlines.
• Collaborative and inclusive, fostering a positive team culture where creativity and innovation thrive.

Skills:

• Deep understanding of the Data Science Lifecycle (DSLC) and the ability to shepherd data science projects from inception to production within the platform architecture.
• Expertise in RAG methodology and AWS Bedrock, Sagemaker, Lex and OpenSearch for developing AI and automation solutions.
• Expertise in the latest GenAI frameworks and tools like DSPy, Letta, LlamaIndex, and LangChain.
• Advanced coding skills in relevant programming languages (Python/JavaScript/TypeScript) and frameworks.
• Similar cloud operations skills as an ML/AI Platform Architect, with an emphasis on workflow automation.

Experience:

• Minimum of 7 years in workflow automation and 2 years at the forefront of the emergence of agentic systems.
• Proven track record of leading complex projects involving ML/AI and automation technologies.
• Demonstrated ability to identify real business and product opportunities and implementing cutting-edge technologies and methodologies in production environments to drive tangible and quantifiable product and business value.
• Experience working with diverse teams to achieve product and organizational objectives through automation.

Education:

• HS Diploma and 8 years of experience in Engineering/IT solutions OR BA/BS Degree and 5 years of experience or equivalent capabilities.
• Preferred Education: M.S. or PhD in Computer Science or related field.
  

In-Office Expectation:

When we put unexpected teams in the same room, we fuel bold thinking with the power to inspire 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.

The annual base pay (or hourly rate of compensation) for this position ranges from $150,405 to $225,607. Hourly and salaried non-exempt employees will also be paid overtime pay when working qualifying overtime hours. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles), to receive a retirement contribution (hourly roles), and commission payment eligibility (sales roles). Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an "at-will position" and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

Why Evinova (AstraZeneca)?

Evinova draws on AstraZeneca's deep experience developing novel therapeutics, informed by insights from thousands of patients and clinical researchers. Together, we can accelerate the delivery of life-changing medicines, improve the design and delivery of clinical trials for better patient experiences and outcomes, and think more holistically about patient care before, during, and after treatment. We know that regulators, healthcare professionals, and care teams at clinical trial sites do not want a fragmented approach. They do not want a future where every pharmaceutical company provides its own, different digital solutions. They want solutions that work across the sector, simplify their workload, and benefit patients broadly. By bringing our solutions to the wider healthcare community, we can help build more unified approaches to how we all develop and deploy digital technologies, better serving our teams, physicians, and ultimately patients. Evinova represents a unique opportunity to deliver meaningful outcomes with digital and AI to serve the wider healthcare community and create new standards for the sector.

Interested? Come and join our journey.

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.

---