Full Stack DeveloperAI Engineer

Contact: Sabrina Garcia -
No 3rd party candidates

Position Overview
The Full Stack Clinical Platform Engineer Digital Transformation will design implement and operate production-grade Generative AI and Machine Learning solutions that support the Global Development Digital Transformation initiative.

This role sits at the intersection of data engineering and applied AI partnering closely with Clinical Operations Data Management Regulatory and IT to design build and maintain modern data platforms and AI-enabled pipelines that underpin the transformation program.

The ideal candidate brings deep expertise in clinical data infrastructure and modern data engineering combined with hands-on experience deploying machine learning solutions in regulated life sciences environments. This role will act as both a technical authority and strategic liaison between transformation projects and enterprise IT ensuring that solutions are scalable compliant and aligned with evolving regulatory and data standards.

Location: New Jersey Preferred. Remote may be considered for highly qualified candidates.

Key Responsibilities

• 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/or fine-tune high-performing Generative AI models and apply modern techniques from relevant published work where appropriate.
• Develop scalable and robust 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 to meet clinical and operational requirements including decisions around retrieval-augmented generation (RAG) vector databases embedding models and LLM providers balancing compliance performance and cost.
• Develop deploy and maintain robust data pipelines for structured and unstructured clinical data integrating internal systems with CRO and external partner data sources and ensuring end-to-end data integrity and traceability.
• Identify and implement opportunities to increase data interoperability and standardization across Global Development systems and other business units reducing manual effort and accelerating data availability for clinical programs.
• Develop and implement automated quality monitoring pipelines for both internal and CRO-sourced clinical data surfacing quality metrics and triggering corrective workflows in alignment with the studys Medical Monitoring Plan.
• Ensure all data solutions comply with applicable regulatory frameworks including HIPAA GDPR and 21 CFR Part 11 and contribute to data governance strategy data lineage documentation and audit readiness.
• Maintain and manage code repositories such as Bitbucket and GitHub with clean well-documented version-controlled code; uphold engineering best practices including code review testing and CI/CD pipelines.

Qualifications

• Advanced degree in computer science biomedical informatics statistics or a closely related field required; PhD with 6 years of relevant experience or MS with 10 years of relevant experience strongly preferred.
• Minimum of 57 years of experience designing implementing and leading data engineering solutions in life sciences or healthcare with demonstrated accountability for end-to-end delivery.
• Demonstrated expertise in designing and maintaining clinical or biomedical data infrastructure including data lake and warehouse architectures optimized for regulatory-grade clinical data.
• Expertise in modern cloud data platforms such as Snowflake Databricks Redshift and BigQuery with proficiency in Python SQL R and related programming languages.
• Proficiency in cloud architecture (AWS Azure or GCP) and DevOps practices including CI/CD containerization (Docker/Kubernetes) and infrastructure-as-code; relevant certifications are a plus.
• Demonstrated experience building scaling and maintaining pipelines for structured and unstructured data with the ability to integrate pipelines across the enterprise.
• Deep knowledge of regulatory frameworks (HIPAA GDPR 21 CFR Part 11) and clinical data standards (CDISC HL7 FHIR) with experience applying them in regulated development environments.
• Hands-on experience developing or integrating machine learning pipelines and working with clinical AI/ML applications such as natural language processing anomaly detection or predictive modeling.
• Strong scientific communication skills with the ability to translate complex technical architectures and outputs into clear strategic recommendations for non-technical clinical and executive stakeholders.
• Experience with data governance frameworks data quality tooling and metadata management practices in clinical or regulated settings.

Ideal Candidate Profile

• A builder at heartsomeone who moves fluidly from whiteboard to working solution and is comfortable owning the full arc from idea through deployed product.
• Able to assess a clinical or operational challenge and independently determine whether and how AI can meaningfully solve itnot simply implement what is handed to them.
• A natural cross-functional collaborator who earns the trust of clinical operations regulatory and IT stakeholders alike and is comfortable operating as both a technical lead and strategic partner.
• Solutions-oriented and innovation-driven with the confidence to constructively challenge legacy thinking and the pragmatism to deliver within the constraints of a regulated environment.
• Thrives in ambiguity and fast-moving environments able to balance long-horizon architectural thinking with near-term delivery commitments across multiple concurrent transformation workstreams.
• A proactive learner who actively monitors advances in AI/ML data engineering and clinical informatics and brings external insights back to accelerate the programs evolution.