Technical Lead

The Technical Lead will provide strategic technical leadership, scientific consulting, and executive-level advisory support to Government leadership for the development, integration, and operationalization of advanced Artificial Intelligence (AI), Machine Learning (ML), and data science capabilities that accelerate cancer research, clinical decision support, and precision medicine.\n \n Serving as the Government’s trusted technical advisor, the Technical Lead will collaborate closely with NCI leadership, principal investigators, biomedical researchers, clinicians, informaticians, and multidisciplinary engineering teams to develop innovative AI-enabled solutions supporting clinical research, scientific data management, and enterprise research platforms.\n \n The successful candidate will combine deep expertise in artificial intelligence, machine learning, biomedical informatics, cloud computing, and modern software engineering with exceptional customer engagement and communication skills to guide technology strategy, influence architectural decisions, and ensure delivery of scalable, secure, and scientifically rigorous AI capabilities aligned with NIH and NCI strategic priorities.\n \n \nKey Responsibilities\n \n \n

• Lead the technical strategy, architecture, and implementation of AI-enabled solutions that support cancer research, precision medicine, clinical research, and enterprise biomedical informatics.\n
• Serve as the principal technical advisor to NCI leadership, providing strategic guidance on AI, ML, biomedical informatics, and digital modernization initiatives.\n
• Partner with Government stakeholders, scientific leadership, and multidisciplinary Subject Matter Experts (SMEs) to define technical priorities, evaluate emerging technologies, and deliver innovative, mission-focused solutions.\n
• Provide technical leadership across AI model development, deployment, and lifecycle management, including machine learning, deep learning, natural language processing (NLP), large language models (LLMs), computer vision, predictive analytics, and multi-agent AI systems.\n
• Oversee the design and integration of AI capabilities supporting biomedical imaging, radiomics, genomics, multi-omics analysis, precision oncology, clinical trial optimization, semantic search, knowledge management, and decision support.\n
• Guide the development of scalable AI and cloud-based architectures leveraging high-performance computing (HPC), AWS, Azure, Google Cloud Platform, Kubernetes, and modern MLOps practices.\n
• Ensure AI solutions adhere to Responsible AI principles, including model governance, explainability (XAI), bias mitigation, security, privacy, and compliance with NIH policies, Executive Orders, and the NIST AI Risk Management Framework.\n
• Lead technical reviews, architecture discussions, executive briefings, and technology roadmaps while effectively communicating complex technical concepts to Government executives, researchers, and business stakeholders.\n
• Mentor engineering teams and provide technical oversight to AI engineers, software developers, data scientists, cloud architects, cybersecurity specialists, and biomedical informatics SMEs to ensure successful delivery of high-quality technical solutions.\n
• Evaluate and recommend emerging AI technologies and innovative approaches that accelerate scientific discovery, improve operational efficiency, and advance NCI’s strategic research mission.\n

• Master’s degree in Computer Science, Artificial Intelligence, Biomedical Informatics, Bioinformatics, Data Science, Computer Engineering, Applied Mathematics, or a related discipline.\n
• Minimum 15 years of progressively responsible technical leadership supporting large-scale Federal health, biomedical research, or scientific computing programs.\n
• Minimum 10 years designing, implementing, and leading enterprise AI and ML solutions within healthcare, biomedical research, life sciences or federal research environments.\n
• Demonstrated experience supporting NIH, NCI, or other Federal biomedical research organizations.\n
• Extensive expertise in deep learning, machine learning, generative AI, NLP, LLMs, computer vision, predictive analytics, biomedical informatics, and cloud-native AI architectures.\n
• Demonstrated experience advising executive Government customers on AI strategy, enterprise architecture, and digital modernization initiatives.\n
• Proven experience leading multidisciplinary teams consisting of AI engineers, data scientists, software engineers, cloud architects, cybersecurity specialists, and biomedical subject matter experts.\n
• Experience with HPC, cloud-native AI platforms, Kubernetes, DevSecOps, and MLOps.\n
• Familiarity with TensorFlow, PyTorch, Scikit-learn, Hugging Face, MLflow, Kubeflow, LangChain, vector databases, graph databases, and AI orchestration frameworks.\n
• Ability to obtain and maintain a Public Trust / ADPII Clearance.\n, * Ph.D. in AI, Biomedical Informatics, Computer Science, Computational Biology, or related field preferred.\n, * Excellent analytical and problem-solving skills.\n
• Ability to lead cross-functional teams in a collaborative environment.\n
• Commitment to quality, innovation, and continuous process improvement.\n
• Ability to communicate effectively with both technical and executive audiences\n

• Experience supporting NCI organizations including CBIIT, CCR, DCTD, DCP, or related biomedical research programs.\n
• Experience with cancer informatics, biomedical imaging, radiomics, genomics, precision oncology, clinical trials, and translational research.\n
• Expertise with FHIR, OMOP, FAIR data principles, biomedical ontologies, semantic interoperability, and research data ecosystems.\n