Data Scientist / AI Engineer

Ironclad Defense Works•Norfolk, VA

2d•$115,000 - $130,000•Onsite

About The Position

Ironclad is seeking an experienced Data Scientist / AI Engineer to support the development and implementation of advanced data science, artificial intelligence, and large language model capabilities within the NATO enterprise. This position requires a technically versatile professional who can bridge data engineering, software development, machine learning, and operational mission requirements. The selected candidate will design scalable data architectures, build and optimize data pipelines, develop API-based infrastructure, and support the secure deployment of AI and machine learning solutions in cloud-based and hybrid environments. The role requires strong hands-on experience with generative AI, large language models (LLMs), distributed systems, microservices, containerized applications, and modern software engineering practices. The successful candidate must also be able to translate complex operational challenges into practical technical solutions for military and civilian stakeholders.

Requirements

Bachelor’s degree or higher from a nationally recognized university in data science, data analytics, artificial intelligence, mathematics, physics, computer science, software engineering, or a closely related discipline.
At least four years of professional experience as a Data Scientist, Machine Learning Engineer, Data Engineer, Software Engineer, or in a closely related role.
Demonstrated experience developing operational AI or machine learning solutions.
Experience with distributed systems and cloud-based or hybrid architectures.
Experience designing API-based infrastructure and microservices architectures.
Hands-on experience developing and deploying containerized applications using technologies such as Docker or Kubernetes.
Demonstrated experience with generative AI and large language models.
Experience preprocessing data and supporting the fine-tuning and deployment of LLMs in secure, scalable environments.
Experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, or comparable technologies.
Strong programming experience with Python, Java, Scala, or similar languages.
Experience with version control, CI/CD pipelines, automated testing, and modern software engineering practices.
Experience building and optimizing ETL processes, data pipelines, and real-time streaming solutions.
Familiarity with Apache Airflow, Kafka, Spark, or comparable data-engineering technologies.
Experience architecting or maintaining data lakes, data warehouses, distributed storage systems, or NoSQL solutions.
Knowledge of platforms such as Delta Lake, Snowflake, Hadoop, or comparable technologies.
Experience applying AI to operational decision support and the analysis of unstructured data, including text or imagery.
Strong understanding of data security, privacy, sovereignty, and responsible AI practices.
Experience developing dashboards, visual reports, and analytics using Tableau, Microsoft Power BI, Kibana, or comparable tools.
Ability to translate operational problems into practical AI and machine learning solutions.
Demonstrated success working with multidisciplinary technical teams.
Strong written and verbal communication skills.
Ability to explain technical concepts to non-technical stakeholders and senior leaders.
Ability to mentor or train personnel in AI engineering, data science, or software development concepts.

Nice To Haves

Familiarity with NATO processes, organizational structures, operational culture, and decision-making procedures.
Experience supporting military, defense, government, or international organizations.
Experience developing AI or data-engineering solutions using open-source frameworks and publicly available datasets.
Familiarity with military staff workflows and operational planning processes.
Experience with federated learning and privacy-preserving collaboration across multiple organizations or nations.
Experience supporting cross-domain data sharing and API-driven interoperability.
Familiarity with agile project-management methods and tools such as JIRA, Trello, or Microsoft Loop.
Experience briefing senior leaders and presenting actionable, data-driven recommendations.
Knowledge of ethical AI principles, including bias mitigation, responsible data handling, transparency, and secure deployment.

Responsibilities

Develop and implement scalable data science and AI capabilities supporting NATO initiatives.
Design, build, and maintain data pipelines for structured and unstructured data.
Prepare, cleanse, transform, and optimize data for LLM training, fine-tuning, inference, and analytics.
Develop API-based infrastructure that integrates LLMs and machine learning models with operational systems.
Design and support microservices and containerized AI/ML applications.
Build distributed data storage and processing solutions using cloud-based or hybrid architectures.
Develop real-time data processing and streaming capabilities for operational decision support.
Automate data engineering processes and improve the scalability, efficiency, and reliability of AI infrastructure.
Implement monitoring, logging, traceability, and performance-optimization tools for data pipelines and APIs.
Support the secure deployment of AI and LLM solutions in Microsoft Azure, AWS, or comparable environments.
Develop tools that improve data accessibility for data scientists, analysts, engineers, and operational users.
Collaborate with data scientists, software engineers, system architects, and other technical stakeholders.
Support federated learning, cross-domain data sharing, and secure collaboration across NATO nations.
Develop proofs of concept for LLM-based and advanced analytics applications.
Evaluate operational requirements and recommend appropriate AI, software, and data-engineering solutions.
Create dashboards, reports, and visual analytics for senior and non-technical stakeholders.
Provide technical briefings, mentoring, and training in AI engineering, data science, API development, and digital literacy.
Research emerging developments in generative AI, distributed computing, data architecture, and software engineering.
Promote responsible, secure, and ethical AI practices throughout solution development and deployment.