Generative AI Cloud Operations Engineer - Evinova (Gaithersburg)

Job Title: Generative AI Cloud Operations Engineer - Evinova
Location: Gaithersburg, MD

At AstraZeneca, we pride ourselves on crafting a collaborative culture that champions knowledge‑sharing, ambitious thinking and innovation – ultimately providing employees with the opportunity to work across teams, functions and even the globe.

Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face‑to‑face in our offices 3 days a week . Our head office is purposely designed with collaboration in mind, providing space where teams can come together to strategize, brainstorm and connect on key projects. Comprehensive relocation packages available for qualified candidates.

Are you ready to be part of the future of healthcare? Can you think big, be bold, and harness the power of digital and AI to tackle longstanding life sciences challenges? Then Evinova, a global health tech business might be for you!

Transform patients’ lives through technology, data, and innovative ways of working. You’re disruptive, decisive, and transformative. Someone excited to use technology to improve patients’ health. We’re building a new Health‑tech business – Evinova, a fully‑owned subsidiary of AstraZeneca Group.

Evinova delivers market‑leading digital health solutions that are science‑based, evidence‑led, and human experience‑driven. Thoughtful 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 pioneering digital solutions that improve the patients’ 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.

Introduction to Role

The Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is a newly formed platform team that will spearhead the design, creation, and operational excellence of our LLM‑based agent deployments, multi‑agent orchestration, and conversational AI systems pipelines to catalyze and accelerate science‑led innovations.

This team is responsible and accountable for the design, implementation, deployment, health and performance of all LLM‑based applications. 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).

As a Generative AI Cloud Operations Engineer for clinical trial design, planning, and operational optimization on our team, you will lead the development and management of AI operations systems for our trial management and optimization SaaS product. You will collaborate closely with our AI Engineers to transition projects from embryonic research into production‑grade AI capabilities, utilizing advanced tools and frameworks to optimize model deployment, governance, and infrastructure performance.

This position requires a deep understanding of cloud‑native agentic Generative AI deployment 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.

Accountabilities

Operational Excellence

• Drive the creation of proactive capability and process enhancements that ensures enduring value creation and analytic compounding interest.
• Design and implement resilient cloud Genereative AI agent operational capabilities to maximize our system A‑abilities (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 Generative AI‑based systems, workloads and processes.

ML/AI Cloud Operations and Engineering

• Develop and manage GenAI Ops systems for clinical trial design, planning and operational optimization.
• Integrate LLM proxies/routers including LiteLLM Proxy/Router or other solutions
• Ensure proper RAG pipeline optimization and scaling
• Integration of token usage, latency, response quality, and hallucination detection tools at a platform level.
• Partner closely with AI Engineers and data scientists to shepherd projects from embryonic research stages into production‑grade agentic Generative AI capabilities.
• Leverage and teach modern tools, libraries, frameworks and best practices to design, validate, deploy and monitor Generative AI agents in production (including LangChain, LangGraph, Google ADK, Langfuse, DSPy, Arize Phoenix, Pinecone, Weaviate, Splunk, Grafana, Prometheus, Xray, and more)
• Enhance system scalability, reliability, and performance through effective infrastructure and process management.
• Ensure that any prediction we make is backed by deep exploratory data analysis and evidence, interpretable, explainable, safe, and actionable.
• Leverage Vertex AI, Azure Foundry, OpenAI, Anthropic, and other foundation model platforms to provide reliable and stable access to LLMs

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.
• Know when to ask for help and when to help others proactively.

Essential Skills/Experience

• HS Diploma or GED
• Minimum of 2 years deploying and maintaining Generative AI agents or GenAI‑based workflows/applications in production.
• Deep understanding of challenges in deploying Generative AI applications and agents.
• Closely follows frontier developments in Generative AI and GenAI tooling, techniques, and technologies.
• Deep understanding of the Data Science Lifecycle (DSLC) and the ability to shepherd data science projects from inception to production within the platform architecture.
• Expert in evals tools for LLMs using tools such as Arize Phoenix, Langfuse, Braintrust, Freeplay, or similar.
• Expert in CDK for python and/or TypeScript
• Strong software engineering abilities in Python/TypeScript
• Expert in AWS services and containerization technologies like Docker and Kubernetes.
• Experience deploying GenAI agents using frameworks such as LangChain, LangGraph, LlamaIndex, Google ADK, or Strands Agents.
• Ability to collaborate effectively with engineering, design, product, and science teams.
• Strong written and verbal communication skills for reporting and documentation.
• Proven track record of deploying algorithms and machine learning models into production environments.
• Demonstrated ability to work closely with cross‑functional teams, particularly data scientists.

Where can I find out more?

• Learn more about Evinova
• Our Social Media, Follow AstraZeneca on LinkedIn
• Follow AstraZeneca on Facebook
• Follow AstraZeneca on Instagram
• Our US Footprint: Powering Scientific Innovation - YouTube

Why Evinova?

Evinova is a global health tech business, separate company part of the AstraZeneca group. 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 life sciences 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. Join us on our journey of building a new kind of health tech business to reset expectations of what a biopharmaceutical company can be. This means we’re opening new ways to work, pioneering cutting‑edge methods, and bringing unexpected teams together. Interested? Come and join our journey.

Total Rewards

The annual base pay for this position ranges from $134,866.40 to $202,299.60.

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 e]]> <