Data Scientist ​/ AI Engineer

Data Scientist / AI Engineer

Location:

Norfolk, Virginia

Employment Type:

Full-time, On-site

Security Clearance:
Active NATO or U.S. National SECRET clearance required

Citizenship:
Must be a citizen of a NATO member nation

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.

• 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.

• 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 Tensor Flow, PyTorch,…