Technical Lead

The Leidos Health & Civil Sector is seeking a Technical Lead to support the National Institutes of Health (NIH) National Cancer Institute (NCI)

** This posting is for future business not yet awarded **

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.

Serving as the Governments 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.

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.

Key Responsibilities

• Lead the technical strategy architecture and implementation of AI-enabled solutions that support cancer research precision medicine clinical research and enterprise biomedical informatics.
• Serve as the principal technical advisor to NCI leadership providing strategic guidance on AI ML biomedical informatics and digital modernization initiatives.
• 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.
• 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.
• 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.
• 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.
• 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.
• Lead technical reviews architecture discussions executive briefings and technology roadmaps while effectively communicating complex technical concepts to Government executives researchers and business stakeholders.
• 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.
• Evaluate and recommend emerging AI technologies and innovative approaches that accelerate scientific discovery improve operational efficiency and advance NCIs strategic research mission.

Required Qualifications

• Masters degree in Computer Science Artificial Intelligence Biomedical Informatics Bioinformatics Data Science Computer Engineering Applied Mathematics or a related discipline.
• Minimum 15 years of progressively responsible technical leadership supporting large-scale Federal health biomedical research or scientific computing programs.
• Minimum 10 years designing implementing and leading enterprise AI and ML solutions within healthcare biomedical research life sciences or federal research environments.
• Demonstrated experience supporting NIH NCI or other Federal biomedical research organizations.
• Extensive expertise in deep learning machine learning generative AI NLP LLMs computer vision predictive analytics biomedical informatics and cloud-native AI architectures.
• Demonstrated experience advising executive Government customers on AI strategy enterprise architecture and digital modernization initiatives.
• Proven experience leading multidisciplinary teams consisting of AI engineers data scientists software engineers cloud architects cybersecurity specialists and biomedical subject matter experts.
• Experience with HPC cloud-native AI platforms Kubernetes DevSecOps and MLOps.
• Familiarity with TensorFlow PyTorch Scikit-learn Hugging Face MLflow Kubeflow LangChain vector databases graph databases and AI orchestration frameworks.
• Ability to obtain and maintain a Public Trust / ADPII Clearance.

Preferred Qualifications

• Ph.D. in AI Biomedical Informatics Computer Science Computational Biology or related field preferred.
• Experience supporting NCI organizations.
• Experience with cancer informatics biomedical imaging radiomics genomics precision oncology clinical trials and translational research.
• Expertise with FHIR OMOP FAIR data principles biomedical ontologies semantic interoperability and research data ecosystems.

Desired Characteristics

• Strong customer focus and mission orientation.
• Excellent analytical and problem-solving skills.
• Ability to lead cross-functional teams in a collaborative environment.
• Commitment to quality innovation and continuous process improvement.
• Ability to communicate effectively with both technical and executive audiences

If youre looking for comfort keep scrolling. At Leidos we outthink outbuild and outpace the status quo because the mission demands it. Were not hiring followers. Were recruiting the ones who disrupt provoke and refuse to fail. Step 10 is ancient history. Were already at step 30 and moving faster than anyone else dares.

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job education experience knowledge skills and abilities as well as internal equity alignment with market data applicable bargaining agreement (if any) or other law.