ClearanceJobs
Software Engineer - AI Application Developer
ClearanceJobs, Virginia Beach, Virginia, us, 23450
AI/ML Software Developer
The candidate should be capable of working independently as a contributor to an agile, full-stack AI/ML software development team. He or she should exhibit expertise in: Strong software architecture and programming skills, with proficiency in Java and Python The design and implementation of end-to-end AI solution, data services, and APIs into production applications Integration of AI models into web and other front end systems, ensuring performance, reliability and user experience to meet stakeholder needs Expertise with Artificial Intelligence, Machine Learning, and Deep Learning for Generative AI and Predictive AI Knowledge of Extract, Translate, and Load (ETL) techniques and procedures AI/MLOps - Model Containerization and deployment, pipeline automations Cloud and Information Technology principles including cloud-based architecture, database architecture, and data sharing protocols The candidate should also demonstrate a general understanding of or interest in gaining expertise in: Systems Engineering processes, methods, and tools as applied to systems lifecycles Digital Engineering methodologies and tooling In this role, the candidate would be collaborating with a software development team on the development and deployment of full-stack artificial intelligence software applications. Day-to-day responsibilities would include the specification, architecting, and development of cloud-based software and infrastructure to support AI/ML use cases. The candidate will be working in a cross-functional team designing, developing and deploying advanced applications in cloud and AI technology. Application development includes integration with commercial and cloud-based software through REST or Open APIs. The candidate will be expected to develop training/validation/test data sets, preprocessing scripts, AI models, and evaluation metrics scripts. Additional Development of software and SI/ML pipelines. Occasionally, customer facing demonstrations of software technology are required. Qualifications: BS 8-10, MS 6-8, PhD 3-5 Must be able to obtain/maintain Secret Clearance Technology and Tools: Software Engineering (Java, Python) Graph-Based/Data Science Skills (PyGraph, Pydantic) Familiarity with cloud security frameworks and compliance requirements (e.g., NIST, DoD STIGs) Proficiency with infrastructure-as-code tools (Terraform, Ansible, CloudFormation) for controlled deployments. AI/MLOps - (Azure AI Studio; AWS Sagemaker, Kubeflow, etc) Familiarity with LLM APIs (OpenAI API, AWS Bedrock/boto) Experience with modern LLM integration methods and applicable tools (LlamaIndex/LangChain): Orchestration frameworks (RAG, Agents, MCP, etc) Retrieval (Vector Search, BM25, Hierarchical, etc) Experience with Software Development lifecycle practices and automations (Pipeline design, management, Git/GitOps, CI/CD, Version Control, Testing) Experience with Infrastructure as Code (AWS CloudFormation, Azure Arm Templates, Terraform) Experience implementing authentication/authorization and role-based access controls (RBAC) Cloud-native technologies and development (Python/FastAPI, SQL, Redis) Command-line (CLI) Proficiency (Bash, PowerShell, etc) Experience integrating software via RESTful APIs, Java APIs, WebSockets, Async Message Queues (Pub/Sub, etc) Preferred Technologies: Software application design and development using UML or SysML Performance Optimization (server-side rendering, code splitting, CSS modules) Systems Engineering processes, methods, and tools as applied to systems lifecycles Digital Engineering methodologies and tooling Equal Pay Act: This is the projected compensation range for this position. There are differentiating factors that can impact a final salary/hourly rate, including, but not limited to, Contract Wage Determination, relevant work experience, skills and competencies that align to the specified role, geographic location (For Remote Opportunities), education and certifications as well as Federal Government Contract Labor categories. In addition, Arcfield invests in its employees beyond just compensation. EEO Statement: We are an equal opportunity employer and federal government contractor. We do not discriminate against any employee or applicant for employment as protected by law.
The candidate should be capable of working independently as a contributor to an agile, full-stack AI/ML software development team. He or she should exhibit expertise in: Strong software architecture and programming skills, with proficiency in Java and Python The design and implementation of end-to-end AI solution, data services, and APIs into production applications Integration of AI models into web and other front end systems, ensuring performance, reliability and user experience to meet stakeholder needs Expertise with Artificial Intelligence, Machine Learning, and Deep Learning for Generative AI and Predictive AI Knowledge of Extract, Translate, and Load (ETL) techniques and procedures AI/MLOps - Model Containerization and deployment, pipeline automations Cloud and Information Technology principles including cloud-based architecture, database architecture, and data sharing protocols The candidate should also demonstrate a general understanding of or interest in gaining expertise in: Systems Engineering processes, methods, and tools as applied to systems lifecycles Digital Engineering methodologies and tooling In this role, the candidate would be collaborating with a software development team on the development and deployment of full-stack artificial intelligence software applications. Day-to-day responsibilities would include the specification, architecting, and development of cloud-based software and infrastructure to support AI/ML use cases. The candidate will be working in a cross-functional team designing, developing and deploying advanced applications in cloud and AI technology. Application development includes integration with commercial and cloud-based software through REST or Open APIs. The candidate will be expected to develop training/validation/test data sets, preprocessing scripts, AI models, and evaluation metrics scripts. Additional Development of software and SI/ML pipelines. Occasionally, customer facing demonstrations of software technology are required. Qualifications: BS 8-10, MS 6-8, PhD 3-5 Must be able to obtain/maintain Secret Clearance Technology and Tools: Software Engineering (Java, Python) Graph-Based/Data Science Skills (PyGraph, Pydantic) Familiarity with cloud security frameworks and compliance requirements (e.g., NIST, DoD STIGs) Proficiency with infrastructure-as-code tools (Terraform, Ansible, CloudFormation) for controlled deployments. AI/MLOps - (Azure AI Studio; AWS Sagemaker, Kubeflow, etc) Familiarity with LLM APIs (OpenAI API, AWS Bedrock/boto) Experience with modern LLM integration methods and applicable tools (LlamaIndex/LangChain): Orchestration frameworks (RAG, Agents, MCP, etc) Retrieval (Vector Search, BM25, Hierarchical, etc) Experience with Software Development lifecycle practices and automations (Pipeline design, management, Git/GitOps, CI/CD, Version Control, Testing) Experience with Infrastructure as Code (AWS CloudFormation, Azure Arm Templates, Terraform) Experience implementing authentication/authorization and role-based access controls (RBAC) Cloud-native technologies and development (Python/FastAPI, SQL, Redis) Command-line (CLI) Proficiency (Bash, PowerShell, etc) Experience integrating software via RESTful APIs, Java APIs, WebSockets, Async Message Queues (Pub/Sub, etc) Preferred Technologies: Software application design and development using UML or SysML Performance Optimization (server-side rendering, code splitting, CSS modules) Systems Engineering processes, methods, and tools as applied to systems lifecycles Digital Engineering methodologies and tooling Equal Pay Act: This is the projected compensation range for this position. There are differentiating factors that can impact a final salary/hourly rate, including, but not limited to, Contract Wage Determination, relevant work experience, skills and competencies that align to the specified role, geographic location (For Remote Opportunities), education and certifications as well as Federal Government Contract Labor categories. In addition, Arcfield invests in its employees beyond just compensation. EEO Statement: We are an equal opportunity employer and federal government contractor. We do not discriminate against any employee or applicant for employment as protected by law.