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Job Description & How to Apply Below
Position Overview
We are looking for a Life Sciences Solutions Engineer who combines strong coding skills with deep expertise in at least one of the following areas:
Pharmaceutical quality systems or quality control.
GxP, computerized‑system compliance, or regulated software validation.
Clinical trial operations, clinical data management, or trial oversight.
This is not a documentation‑only compliance role. You will inspect data, write code, configure and test systems, and work directly with engineers, clinical teams, quality specialists, and business stakeholders. You will guide the introduction of production‑grade AI and data systems into regulated workflows.
What You Will Do
Translate pharmaceutical and clinical requirements into implementable data models, workflows and access rules.
Guide software deployment through the applicable quality, privacy, security, and regulatory requirements.
Determine which regulatory frameworks apply to each use case rather than treating every healthcare system as subject to identical controls.
Analyze clinical trial data covering studies, sites, subjects, visits, forms, observations, queries, reviews, medical coding, and audit history.
Define and test controls for sensitive information, including role‑based access, separation of duties, approvals, and audit trails.
Produce and maintain documentation such as intended‑use definitions, risk assessments, traceability matrices, validation plans, test evidence, operating procedures, and change records.
Work with quality, clinical, security, legal, and engineering stakeholders to resolve differences between written procedures and actual system behavior.
Support technical workshops, deployment planning, validation, training, and post‑deployment reviews.
What We Are Looking For
5+ years of professional experience in software engineering, data engineering, solutions architecture, technical consulting, or a comparable hands‑on technical role.
Deep professional expertise in at least one of pharmaceutical quality, regulated computerized systems, or clinical trials.
Strong coding skills, preferably in Python, together with practical SQL and data‑modeling experience.
Ability to understand complex data pipelines and trace how a source record is transformed, connected, exposed, and audited.
Ability to communicate effectively with software engineers and specialists from quality, clinical operations, data management, and compliance.
Experience in a pharmaceutical, biotechnology, healthcare, CRO, technology consultancy, or regulated cloud/software environment.
Strong professional English and the ability to produce precise technical and validation documentation.
High daily engagement with modern AI tools and an interest in the responsible deployment of agent‑based systems.
Relevant Areas of Expertise
Candidates are not expected to know every framework below, but should have substantial practical experience in those relevant to their previous work:
ICH Good Clinical Practice and clinical trial data governance.
GxP and pharmaceutical quality systems.
Computerized‑system validation and risk‑based Computer Software Assurance.
EU Annex 11 and FDA 21 CFR Part 11.
GDPR and health‑data access controls.
ALCOA+ data‑integrity principles.
Clinical data management, electronic data capture, source‑data review, clinical queries, coding, and trial audit trails.
EU medical‑device or software regulation where applicable to a system’s intended use.
Quality risk management, change control, deviation management, CAPA, and supplier qualification.
Nice to Have
Experience delivering infrastructure, data, or AI platforms for pharmaceutical customers.
Familiarity with clinical data standards such as CDISC ODM, SDTM, or ADaM.
Experience with electronic data‑capture systems, clinical trial management systems, quality‑management systems, laboratory systems, or regulatory document platforms.
Knowle…
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