Systems Planning & Analysis
Data Scientist/AI Engineer
Systems Planning & Analysis, Norfolk, Virginia, United States, 23500
Overview
Systems Planning and Analysis, Inc. (SPA) delivers high-impact, technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, in both the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunity, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted. We have a near-term need for a Data Scientist/AI Engineer to provide onsite support in Norfolk, VA. Responsibilities
The Data Scientist/AI Engineer at NATO ACT will contribute to the development and implementation of an enabling data science and AI capability at HQ SACT and across the NATO Enterprise, with a specific focus on scalable data engineering and software systems to support AI initiatives. Design, develop, and maintain robust data pipelines and architectures to manage the ingestion, transformation, and processing of structured and unstructured data for large Language Model (LLM)-based applications and other AI systems. Lead efforts to optimize data delivery and automate data engineering processes, proposing enhancements to infrastructure to improve scalability, efficiency, and reliability in support of LLM deployments. Build API-based infrastructure and frameworks that enable seamless integration of LLMs and ML models with operational systems, ensuring performance, security, and interoperability with NATO environments. Support the development, testing, and validation of microservices and containerized applications to operationalize AI/ML capabilities, including deployment of LLM use cases within NATO. Implement distributed data storage and processing systems (cloud-based or hybrid) that align with NATO standards and enable scalable use of LLMs across the enterprise. Develop tools and systems to improve data accessibility, enabling data scientists and analysts to efficiently interact with and query data for training, inference, and analytics. Coordinate with data scientists, software engineers, and system architects to align data engineering workflows with broader AI/ML objectives, ensuring timely delivery of clean, high-quality data for LLM training and inference. Establish mechanisms for real-time data processing and streaming, enabling LLMs to operate effectively in dynamic and responsive applications, such as operational decision support or strategic analysis. Conduct preprocessing, cleansing, and transformation of raw data into formats optimized for training, fine-tuning, and inference within LLM infrastructure. Implement robust monitoring, logging, and performance optimization tools for data pipelines and APIs, ensuring reliability and traceability of LLM-enabled workflows. Collaborate with teams to support federated learning approaches and cross-domain data sharing, ensuring compliance with NATO data sovereignty, security, and ethical guidelines. Provide subject matter expertise on data engineering and software development to staff within HQ SACT or the NATO Enterprise, and develop proofs of concept for LLM-based applications as directed. Research, recommend, and implement best practices for deploying LLMs in secure, cloud-based environments such as Microsoft Azure or AWS, while considering NATO-specific data policies and standards. Evaluate operational requirements and objectives, recommending appropriate engineering solutions for integrating LLMs into NATO workflows and systems. Stay abreast of new developments in AI engineering, including innovations in LLM technologies, data architectures, distributed computing, and API development, to bring cutting-edge capabilities into implementation within NATO. Provide technical training and mentoring to NATO staff, supporting educational efforts in AI engineering, data pipeline design, API development, and digital literacy. Foster a culture of innovation and data-driven decision-making across NATO by building scalable systems that enable the effective exploitation of LLMs and advanced analytics. Qualifications
Required
Citizenship of one of the NATO member countries. Active NATO Secret-level security clearance or valid national Secret clearance. Bachelor’s degree or higher in Data Science, Data Analytics, AI engineering, or related disciplines, or 4+ years of professional data science experience within the last 5 years. 4+ years of proven work experience as a Data Scientist, Machine Learning Engineer, Data Engineer, or Software Engineer, with emphasis on distributed systems, cloud-based architectures, operational AI/ML solutions, API-based infrastructures, microservices, and containerized applications (e.g., Docker, Kubernetes). Demonstrated experience working with GenAI, in particular LLMs, including preprocessing data, fine-tuning, and deployment in secure and scalable environments with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Proven expertise in programming languages such as Python, Java, or Scala, with experience in software engineering practices (version control, CI/CD pipelines, containerization). Experience building and optimizing data pipelines, ETL processes, and real-time streaming solutions using tools like Apache Airflow, Kafka, Spark, or equivalent. Knowledge of applied AI principles for operational decision support and analytics of unstructured data (e.g., text, imagery). Ability to architect and maintain scalable data lakes, data warehouses, or distributed storage systems (e.g., Delta Lake, Snowflake, Hadoop, or NoSQL). Understanding of data security, privacy, and sovereignty issues, particularly in military or international environments, ensuring NATO compliance. Experience building reports, dashboards, and analytics using tools such as Tableau, MS Power BI, or Kibana for high-level stakeholders. Professional experience in NATO environments or familiarity with NATO processes, culture, and decision-making structures. Ability to translate operational problems into practical AI/ML solutions for military and civilian teams. Proven ability to collaborate within multidisciplinary teams, coordinating with data scientists, software engineers, and system architects on cross-functional projects. Strong oral and written communication skills, with ability to brief non-technical audiences and mentor staff in AI engineering, data science, and software development concepts. Available to work onsite based on client needs. Desired
Experience leveraging open-source frameworks and public datasets to develop AI and data engineering solutions. Proficiency in presenting data-driven insights clearly to non-technical audiences, crafting actionable recommendations for senior leadership. Understanding of military staff workflows and federated learning techniques for secure cross-NATO collaboration while preserving dataset sovereignty. Exposure to agile project management methods and tools (e.g., Loop, JIRA, Trello). Eligibility for NATO security clearance and experience working with classified or sensitive data. Exposure to cross-domain data sharing and API-driven interoperability, with attention to security and ethical guidelines in military environments. Familiarity with ethical AI development, bias mitigation, responsible data handling, and alignment with NATO’s ethical AI frameworks.
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Systems Planning and Analysis, Inc. (SPA) delivers high-impact, technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, in both the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunity, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted. We have a near-term need for a Data Scientist/AI Engineer to provide onsite support in Norfolk, VA. Responsibilities
The Data Scientist/AI Engineer at NATO ACT will contribute to the development and implementation of an enabling data science and AI capability at HQ SACT and across the NATO Enterprise, with a specific focus on scalable data engineering and software systems to support AI initiatives. Design, develop, and maintain robust data pipelines and architectures to manage the ingestion, transformation, and processing of structured and unstructured data for large Language Model (LLM)-based applications and other AI systems. Lead efforts to optimize data delivery and automate data engineering processes, proposing enhancements to infrastructure to improve scalability, efficiency, and reliability in support of LLM deployments. Build API-based infrastructure and frameworks that enable seamless integration of LLMs and ML models with operational systems, ensuring performance, security, and interoperability with NATO environments. Support the development, testing, and validation of microservices and containerized applications to operationalize AI/ML capabilities, including deployment of LLM use cases within NATO. Implement distributed data storage and processing systems (cloud-based or hybrid) that align with NATO standards and enable scalable use of LLMs across the enterprise. Develop tools and systems to improve data accessibility, enabling data scientists and analysts to efficiently interact with and query data for training, inference, and analytics. Coordinate with data scientists, software engineers, and system architects to align data engineering workflows with broader AI/ML objectives, ensuring timely delivery of clean, high-quality data for LLM training and inference. Establish mechanisms for real-time data processing and streaming, enabling LLMs to operate effectively in dynamic and responsive applications, such as operational decision support or strategic analysis. Conduct preprocessing, cleansing, and transformation of raw data into formats optimized for training, fine-tuning, and inference within LLM infrastructure. Implement robust monitoring, logging, and performance optimization tools for data pipelines and APIs, ensuring reliability and traceability of LLM-enabled workflows. Collaborate with teams to support federated learning approaches and cross-domain data sharing, ensuring compliance with NATO data sovereignty, security, and ethical guidelines. Provide subject matter expertise on data engineering and software development to staff within HQ SACT or the NATO Enterprise, and develop proofs of concept for LLM-based applications as directed. Research, recommend, and implement best practices for deploying LLMs in secure, cloud-based environments such as Microsoft Azure or AWS, while considering NATO-specific data policies and standards. Evaluate operational requirements and objectives, recommending appropriate engineering solutions for integrating LLMs into NATO workflows and systems. Stay abreast of new developments in AI engineering, including innovations in LLM technologies, data architectures, distributed computing, and API development, to bring cutting-edge capabilities into implementation within NATO. Provide technical training and mentoring to NATO staff, supporting educational efforts in AI engineering, data pipeline design, API development, and digital literacy. Foster a culture of innovation and data-driven decision-making across NATO by building scalable systems that enable the effective exploitation of LLMs and advanced analytics. Qualifications
Required
Citizenship of one of the NATO member countries. Active NATO Secret-level security clearance or valid national Secret clearance. Bachelor’s degree or higher in Data Science, Data Analytics, AI engineering, or related disciplines, or 4+ years of professional data science experience within the last 5 years. 4+ years of proven work experience as a Data Scientist, Machine Learning Engineer, Data Engineer, or Software Engineer, with emphasis on distributed systems, cloud-based architectures, operational AI/ML solutions, API-based infrastructures, microservices, and containerized applications (e.g., Docker, Kubernetes). Demonstrated experience working with GenAI, in particular LLMs, including preprocessing data, fine-tuning, and deployment in secure and scalable environments with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Proven expertise in programming languages such as Python, Java, or Scala, with experience in software engineering practices (version control, CI/CD pipelines, containerization). Experience building and optimizing data pipelines, ETL processes, and real-time streaming solutions using tools like Apache Airflow, Kafka, Spark, or equivalent. Knowledge of applied AI principles for operational decision support and analytics of unstructured data (e.g., text, imagery). Ability to architect and maintain scalable data lakes, data warehouses, or distributed storage systems (e.g., Delta Lake, Snowflake, Hadoop, or NoSQL). Understanding of data security, privacy, and sovereignty issues, particularly in military or international environments, ensuring NATO compliance. Experience building reports, dashboards, and analytics using tools such as Tableau, MS Power BI, or Kibana for high-level stakeholders. Professional experience in NATO environments or familiarity with NATO processes, culture, and decision-making structures. Ability to translate operational problems into practical AI/ML solutions for military and civilian teams. Proven ability to collaborate within multidisciplinary teams, coordinating with data scientists, software engineers, and system architects on cross-functional projects. Strong oral and written communication skills, with ability to brief non-technical audiences and mentor staff in AI engineering, data science, and software development concepts. Available to work onsite based on client needs. Desired
Experience leveraging open-source frameworks and public datasets to develop AI and data engineering solutions. Proficiency in presenting data-driven insights clearly to non-technical audiences, crafting actionable recommendations for senior leadership. Understanding of military staff workflows and federated learning techniques for secure cross-NATO collaboration while preserving dataset sovereignty. Exposure to agile project management methods and tools (e.g., Loop, JIRA, Trello). Eligibility for NATO security clearance and experience working with classified or sensitive data. Exposure to cross-domain data sharing and API-driven interoperability, with attention to security and ethical guidelines in military environments. Familiarity with ethical AI development, bias mitigation, responsible data handling, and alignment with NATO’s ethical AI frameworks.
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