Clinical AI & Automation Engineer
Ship production-grade LLM and automation systems that accelerate eSource-to-EDC workflows — with the validation rigor and audit traceability that clinical research demands.
About the role
Nexa Trials is building the next generation of clinical trial automation — and we need engineers who understand both modern AI tooling and the constraints of GCP-regulated environments. Based in our Lahore delivery center, you will develop LLM-assisted mapping, document extraction, and workflow automation that integrates with NexaSource™, Nexa Bus™, and NexaScheduler™.
Unlike generic AI product teams, we operate inside live studies. Every feature you ship must be explainable, version-controlled, and safe to deploy when coordinators are capturing patient data. You will work closely with data architects in Austin, QC analysts in Dubai, and clinical operations in Canada to ensure automation accelerates work without compromising data integrity.
This is a hybrid engineering role with regular collaboration across US, UAE, and Canadian time zones. You will report to the Engineering Lead in Lahore and contribute to our clinical AI roadmap — from RAG pipelines over protocol documents to validated auto-mapping suggestions for EDC builds.
Responsibilities
- Design and implement LLM-powered tools for CRF-to-eSource mapping suggestions, protocol parsing, and clinical document extraction
- Build RAG pipelines over study artifacts — protocols, IBs, lab manuals, and mapping specs — with retrieval quality tuned for clinical terminology
- Develop Python services and data pipelines that connect AI outputs to Nexa Bus transfer logic and NexaSource form builders
- Implement validation frameworks for AI-assisted outputs — confidence scoring, human-in-the-loop review queues, and regression test suites
- Collaborate with data architects on structured schemas that make LLM outputs auditable and diffable across protocol amendments
- Optimize inference cost, latency, and reliability for production workloads serving multi-site study portfolios
- Document model versions, prompt templates, training data boundaries, and deployment procedures for sponsor audit readiness
- Participate in code review, sprint planning, and cross-region engineering syncs with Austin and Dubai teams
- Stay current on clinical NLP, FHIR-aware extraction, and responsible AI practices in regulated industries
Requirements
- 3+ years of software engineering experience with strong Python proficiency
- Hands-on experience building LLM applications — prompt engineering, RAG, embeddings, and API integration with major model providers
- Working knowledge of clinical data concepts — CRFs, visit schedules, EDC fields, or eSource capture workflows
- Experience designing data pipelines (ETL/ELT) with structured validation and error handling
- Familiarity with vector databases, document chunking strategies, and retrieval evaluation
- Comfort writing technical documentation and test cases for features subject to QA review
- Strong communication skills for async collaboration across global teams
- Eligible to work in Pakistan
Nice to have
- Prior experience in clinical research, health tech, or other regulated data environments
- Exposure to CDISC, OMOP, or FHIR data models
- Experience with fine-tuning, evaluation harnesses, or ML observability for LLM systems
- Knowledge of ICH-GCP and ALCOA+ data integrity principles
- TypeScript or frontend skills for building internal review UIs
- Cloud deployment experience (AWS, Azure, or GCP) with CI/CD pipelines
- Contributions to open-source NLP or clinical informatics projects
What we offer
Work on AI problems that matter — reducing coordinator duplicate entry and study startup time for real patients and sponsors. Lahore is Nexa Trials' engineering hub, and you will have direct access to product leadership and live study feedback loops.
- Competitive compensation and benefits aligned with Lahore tech market
- Hybrid work model with modern office infrastructure
- Ownership of high-impact clinical AI features from prototype to production
- Mentorship from senior engineers and data architects across Austin and Lahore
- Training budget for AI/ML courses, conferences, and clinical research fundamentals
- Clear growth path toward senior engineer, tech lead, or clinical AI architect roles