Senior AI/ML & Cloud Native Software Engineer

Parallax Advanced Research•Beavercreek, OH

9h•Onsite

About The Position

At Parallax Advanced Research, our work is rooted in innovation, collaboration, and national impact. As a nonprofit research institute, we partner with government, academic, and industry clients to solve complex challenges in AI, aerospace, human-machine teaming, and beyond. Parallax Advanced Research Mission is to deliver innovative research and provide technology, human and business solutions via The Science of Intelligent Teaming™ for government, industry and academic clients. Parallax uses agile software development methods to deliver customized research and development software products in support of Air Force and other service missions. The Senior AI/ML & Cloud-Native Software Engineer will support the NASIC Transformation Collection within the Services of Common Concern (SoCC). This position focuses on the design, development, maintenance, and enhancement of AI/ML services and related cloud-native capabilities, including AI/ML Service, Advanced Architecture Environment (AAE) Development, Legacy Data Migration, Data Fabrication/Custom Dataflows, and Cross Domain/NASIC Object Transfer Service (NOTS). The engineer will build and sustain a scalable AI/ML software stack, integrate modern analytic tools, support multiple mission product lines, and deploy solutions into the NASIC Unified Cloud (NUC) and other Department of the Air Force (DAF) cloud environments using the Scrum framework.

Requirements

US Citizenship REQUIRED
Active TS/SCI Clearance and maintenance REQUIRED
Bachelor’s degree in Computer Science or related technical field with experience (10+ years) in software development
Proficiency in at least one modern programming language commonly used for AI/ML and microservices (e.g., Python, Java).
Hands-on experience with at least one major AI/ML framework (e.g., TensorFlow, PyTorch, Scikit-learn).
Experience with MLOps practices and tools (e.g., MLFlow, Kubeflow, or similar) for managing the AI/ML lifecycle.
Strong background in containerization (e.g., Docker) and orchestration (e.g., Kubernetes or equivalent).
Experience designing and operating CI/CD pipelines (e.g., GitLab CI, Jenkins, GitHub Actions, or similar) for multi-environment deployments.
Data engineering experience, including ETL/ELT, custom dataflows, and integration of diverse data sources.
Experience with secure software development and DevSecOps concepts, including code scanning, vulnerability management, and compliance in multi-enclave environments.
Familiarity with integrating FOSS, COTS, and GOTS solutions into an enterprise technology stack.
8 years in software engineering, with at least 5 years in DevSecOps and AI/ML
Proven track record of embedding security in software development
Demonstrated ability to mentor, lead projects, and influence technical direction
Strong written and verbal communication skills for cross-team collaboration

Nice To Haves

MS in Computer Science or related technical field
Experience working within NASIC, Air Force Intelligence, or broader Intelligence Community environments.
Familiarity with cross-domain solutions (CDS) and multi-level security concepts (NIPR/SIPR/JWICS).
Experience with event-driven architectures (e.g., Kafka or similar technologies).
Prior experience integrating with identity and access management (ICAM), data cataloging, collaboration services, or enterprise content/product authoring systems.
Knowledge of applicable DoD/IC security controls, STIG requirements, and accreditation processes.

Responsibilities

Design, implement, and maintain scalable, maintainable, and shareable AI/ML models in alignment with government-approved datasets and requirements.
Develop and maintain a scalable AI/ML software stack supporting the full AI/ML lifecycle (data ingestion, training, evaluation, deployment, monitoring).
Implement reproducible training and evaluation pipelines, documenting procedures and results to support auditability and compliance reviews.
Define and implement model retraining triggers, update procedures, and versioning practices to ensure ongoing model accuracy and reliability.
Integrate modernized analytic tools into AI/ML capabilities and expose them through easy-to-use interfaces for mission users.
Implement model monitoring capabilities, including user-enabled monitoring, model drift detection, and model demand tracking.
Adhere to industry-accepted AI/ML development principles, including transparency, accountability, and responsible use of data and AI/ML.
Design and implement scalable, cloud-native applications and services using containerization and microservices patterns consistent with NASIC’s approved technology stack.
Integrate and deploy code and containers into the NASIC Unified Cloud (NUC) via the established CI/CD pipeline across multiple security enclaves (NIPRnet, SIPRnet, JWICS) and other cloud architectures such as DAF CLOUDworks.
Ensure secure, reliable, and repeatable deployment processes in accordance with DevSecOps best practices and applicable security/compliance standards.
Design and implement data ingestion, transformation, and custom dataflow pipelines to support AI/ML workloads and Transformation Collection services.
Plan and execute legacy data migration into modern architectures and cloud environments, ensuring data quality, integrity, and traceability.
Leverage diverse, relevant data sources and data types for AI/ML models, including establishing connections to future data sources as needed.
Provide and manage access to datasets required for training, testing, and validating AI/ML models, ensuring that all data preparation steps are fully documented and reproducible.
Develop and integrate Transformation Collection services (AI/ML Service, AAE Development, Legacy Data Migration, Data Fabrication/Custom Dataflow, NOTS) to promote and enhance data/product exchange and event-driven architecture.
Integrate capabilities with Integration Services, ICAM Services, Catalog Services, Collaboration Services, and Enterprise Product Authoring Service (EPAS).
Collaborate with mission application teams to enable data services across NASIC and the Air Force Intelligence Community (AF IC).
Assess and document the existing Transformation Collection software baseline and identify modernization, refactoring, and integration opportunities.
Evaluate and integrate Free-and-Open-Source-Software (FOSS), Commercial-Off-The-Shelf (COTS), and Government-Off-The-Shelf (GOTS) solutions consistent with the NASIC approved technology stack.
Ensure all software deliveries and modifications are submitted to the NASIC Depot in accordance with NASIC policies (no unapproved contractor repositories).
Perform maintenance, sustainment, and minor enhancements (MS&E) on delivered operational software within the Transformation Collection.
Refactor and improve existing codebases to enhance performance, reliability, maintainability, and security.
Troubleshoot and resolve issues in production and pre-production environments, working closely with government and contractor teams.
Work within the Scrum framework as described in the NASIC Software Development Guide (SDG), participating in all Scrum ceremonies (sprint planning, daily stand-ups, sprint reviews, retrospectives).
Collaborate with Product Owners and stakeholders to refine, estimate, and implement backlog items.
Develop high-quality technical documentation, including architecture descriptions, data pipeline documentation, AI/ML training and evaluation documentation, deployment runbooks, and user enablement materials.
Support required contract deliverables (CDRLs) and compliance documentation related to Transformation Collection services.