What are the responsibilities and job description for the AI Integration engineer with Security Clearance position at KriaaNet Inc?
Deep proficiency in designing, training, validating, and optimizing machine learning and deep learn-ing models, including supervised, unsupervised, and reinforcement learning techniques. Expertise with industry-standard frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, and associated MLOps toolchains is essential.
- Strong software engineering capabilities, including advanced programming skills in Python and expe-rience developing AI-enabled applications within Linux-based environments. Familiarity with backend frameworks such as Django, asynchronous task queues such as Celery, and database systems including PostgreSQL is required Ability to integrate AI capabilities into legacy and modern systems, with strong knowledge of cloud computing architectures (AWS GovCloud, Azure IL5/6), containerized services (Kubernetes, Docker), and modern API/interface standards (REST, GraphQL, MQTT). Experience deploying AI services in secure, distributed, or hybrid environments is highly desirable.
- Expertise in data acquisition, preparation, and modeling from heterogeneous sources. Skills should include data wrangling, feature engineering, ETL pipeline development, and the use of big data tools such as Apache Spark, Databricks, Hadoop ecosystems, and enterprise data platforms.
- Familiarity with full-stack development concepts to support AI system integration, including working knowledge of HTML, CSS, JavaScript fundamentals, and secure web application design principles.
- Demonstrated understanding of secure coding practices, and industry standards e.g. ISO 27001 for cybersecurity considerations for AI/ML systems. Personnel must be capable of securing AI pipelines and ensuring compliance with DoD AI Ethical Principles.
- Proficiency in modern CI/CD pipelines and DevSecOps methodologies for agile AI development. Can-didates should understand version control (Git), automated testing, infrastructure-as-code, container orchestration, and deployment automation tools.
- Strong technical writing, documentation, and communication skills to produce training materials, system documentation, and operational guidance for non-technical Air Force personnel. Ability to translate complex AI workflows into mission-relevant language is essential.