> Markdown version of [/jobs/ext/2717970-sr-mngr-full-stack-clinical-platform-engineer](https://www.wearedevelopers.com/jobs/ext/2717970-sr-mngr-full-stack-clinical-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Mngr, Full Stack Clinical Platform Engineer - **Company:** Eliassen Group - **Location:** Phoenix, AZ, United States (Remote available) - **Experience:** Expert - **Salary:** $187,200.0 - $228,800.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, BigQuery, Health Informatics, Clinical Data Repository, Cloud Engineering, Code Review, Continuous Integration, Data Governance, Data Infrastructure, Data Integrity, Data Transformation, DevOps, R (Programming Language), Python (Programming Language), Machine Learning, Meta-Data Management, Software Construction, Software Deployment, SQL Databases, Unstructured Data, Fast Healthcare Interoperability Resources, Large Language Models, Snowflake, Generative AI, Data Strategy, Containerization, Data Lakes, Kubernetes, Information Technology, Data Lineage, Health Level Seven International, Enterprise Integration, Data Management, Machine Learning Operations, Data Pipelines, Docker, Amazon Redshift, Databricks - **Published:** September 4, 2026 - **Apply:** https://www.phoenixjobs.com/job.asp?id=3377320450&tx=YT404CYZ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Advanced degree in computer science, biomedical informatics, statistics, or a related field. MS with 6+ years of relevant experience preferred. * 5-7 years of experience leading data engineering solutions in life sciences or healthcare with end-to-end delivery accountability. * Expertise in clinical or biomedical data infrastructure including data lakes and warehouses optimized for regulatory-grade clinical data. * Experience with modern cloud data platforms such as Snowflake, Databricks, Redshift, or BigQuery. Proficiency in Python, SQL, and R. * Proficiency in cloud architecture on AWS, Azure, or GCP and DevOps practices including CI/CD, containerization with Docker or Kubernetes, and infrastructure-as-code. * Experience building and maintaining pipelines for structured and unstructured data with enterprise integration. * Deep knowledge of HIPAA, GDPR, 21 CFR Part 11, and clinical data standards such as CDISC, HL7, and FHIR. * Hands-on experience with machine learning pipelines and clinical AI/ML applications including NLP, anomaly detection, or predictive modeling. * Strong communication skills to translate technical architectures and outputs into clear recommendations for non-technical stakeholders. * Experience with data governance frameworks, data quality tooling, and metadata management in regulated settings., Advanced degree in computer science, biomedical informatics, statistics, or a related field. MS with 6+ years of relevant experience preferred. ## Description * Translate ambiguous clinical and operational problems into well-scoped AI solutions from problem framing and data assessment through prototype, validation, and production deployment. * Design and implement MLOps/LLMOps pipelines to deploy, monitor, and manage large language models in production environments following software engineering best practices. * Collaborate with data scientists to deploy and fine-tune Generative AI models and apply modern techniques from relevant published work where appropriate. * Develop scalable data and ML pipelines for ingestion, preprocessing, validation, training, evaluation, and model deployment across the clinical development ecosystem. * Evaluate and recommend AI tools and frameworks including RAG, vector databases, embedding models, and LLM providers, balancing compliance, performance, and cost. * Develop, deploy, and maintain pipelines for structured and unstructured clinical data, integrating internal systems with CRO and external partner data sources while ensuring data integrity and traceability. * Increase data interoperability and standardization across Global Development systems and other business units to reduce manual effort and accelerate data availability. * Implement automated quality monitoring pipelines for internal and CRO-sourced clinical data, surfacing metrics and triggering corrective workflows aligned with Medical Monitoring Plans. * Ensure compliance with HIPAA, GDPR, and 21 CFR Part 11. Contribute to data governance strategy, data lineage documentation, and audit-readiness. * Maintain code repositories with clean, well-documented, version-controlled code. Uphold engineering best practices including code review, testing, and CI/CD pipelines. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [ZEISS & Microsoft - Building the Next Generation Medical Ecosystem in the Cloud](https://www.wearedevelopers.com/videos/424-zeiss-microsoft-building-the-next-generation-medical-ecosystem-in-the-cloud) - [Making Data Warehouses fast. 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