Ascend Technologies Group · 4 hours ago
Clinical AI Data Engineer
United States
Full-time
Remote
Senior Level
$130K/yr - $170K/yr
5+ years expAscend Technologies Group is a U.S.-based provider of managed IT and cloud services, specializing in telecom and data solutions. They are seeking a Clinical AI Data Engineer to build production-grade LLM systems for extracting and structuring cancer-related data from electronic health records.
Cloud Data ServicesCyber SecurityInformation TechnologyVoIP
Responsibilities
Build Production LLM Systems for Oncology Data Extraction Design and deploy AI systems that reliably extract oncology-specific information from clinical notes and reports, including staging classifications, biomarker results, treatment regimens, and patient and outcomes
Develop Robust AI Agents for Medical Reasoning Create AI agents that handle complex clinical tasks: multi-document synthesis across patient charts, precise entity and relationship extraction for cancer phenotypes, and long-context understanding of treatment histories spanning years. Navigate the nuances of oncology terminology and clinical reasoning patterns
Ensure Clinical Accuracy and Reliability Develop strategies to minimize hallucinations, improve factual consistency, and gracefully handle ambiguous or incomplete clinical documentation. Build evaluation frameworks that measure precision, recall, and clinical validity against gold-standard oncology annotations
Master Oncology EHR Data Structures Work deeply with cancer-specific EHR data including pathology reports, radiology imaging summaries, genomic test results, and treatment documentation. Understand relationships between diagnosis codes, medication orders, lab values, and clinical narratives
Drive Technical Excellence Through LLM Experimentation Establish benchmarking standards and evaluation metrics for clinical NLP models. Experiment with advanced prompting techniques, retrieval-augmented generation, fine-tuning approaches, and multi-agent architectures. Conduct hands-on analysis to identify edge cases, model drift, and opportunities for improvement
Bridge Clinical and Technical Domains Collaborate with oncologists, clinical data abstraction leads, and product managers to translate complex clinical requirements into technical solutions, iterating based on real-world feedback
Qualification
Required
5+ years writing production Python code with proven experience shipping AI/ML systems to production
3+ years hands-on experience with LLMs —including advanced prompt engineering, function calling, agent frameworks, retrieval strategies, fine-tuning, systematic failure mode analysis, and developing intuition for achieving reliable results in production environments
Deep oncology EHR expertise: Strong understanding of cancer EHR data structures, oncology terminologies (ICD-O, SNOMED, AJCC staging, RECIST criteria), clinical documentation workflows, and how oncology data flows through health systems
Advanced NLP and semantic understanding: Deep expertise in information extraction, entity recognition, relationship mapping, and clinical NLP challenges specific to cancer care documentation
Production AI agent experience: You've built agents that work reliably in real-world clinical environments, not just demos—with practical experience handling multi-step reasoning, tool use, and error recovery
Clinical reasoning skills: Ability to understand oncology treatment pathways, interpret clinical notes, and recognize clinically meaningful patterns in unstructured documentation
Scientific approach: You formulate hypotheses, design rigorous experiments, and iterate based on empirical evidence
Clear communicator: Can explain complex technical tradeoffs to both clinical stakeholders and non-technical audiences
Ability to thrive in a fast-paced, collaborative, and remote-first environment
Preferred
Experience with Snowflake or similar data warehouse platforms
Direct experience working with oncology EHR data
Familiarity with NGS data interpretation, and precision oncology concepts
Experience with knowledge graphs and relationship mapping in medical contexts
Familiarity with SOC-2, HIPAA, or sensitive healthcare data handling requirements
Master's or PhD in computational biology, bioinformatics, or related quantitative field
Knowledge of cancer treatment guidelines (NCCN, ASCO) and oncology clinical workflows
Company
Ascend Technologies Group
Ascend Technologies Group delivers IT consulting, cloud solutions, managed support, and cybersecurity for business clients.
11-50 employees
H1B Sponsorship
Ascend Technologies Group has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
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2025 (1)
Funding
Current Stage
Early StageLeadership Team
Jason Baroff
Managing Partner
Recent News
Seattle TechFlash
2025-09-22
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