Software Engineer - AI DevOps Specialist

Responsibilities Roles and Responsibilities The candidate should be capable to work independently as a contributor to an agile AI/ML software development team. He or she should exhibit expertise in: • Expertise in Software Cloud and Database Deployment and Management - Package, release, and deploy AI-enabled applications into secure, scalable environment (Gov Cloud, Air-gapped). • Testing and Quality Assurance - Implement and maintain automated test frameworks and technologies (e.g., PyTest, Postman, Selenium, JUnit) to validate software functionality, performance, and reliability across environments. • AI Application Design & Development - Design, develop and integrate cloud-based applications leveraging Azure and AWS AI/ML services (e.g., OpenAI, Bedrock), and related APIs, with a focus on generative AI models and large language model integration • Integration - Connect AI services with front-end applications, back-end systems, and client APIs to deliver end-to-end solutions. • Security and Compliance Oversight - Ensure software, infrastructure and deployment practices comply with government and industry standards (e.g., NIST, FedRAMP, OWASP) • Stakeholder Engagement - Communicate technical progress, risks, and solutions clearly with stakeholders and team members. • Continuous Improvement - Stay current with evolving Azure and AWS AI services, bringing forward best practices and new capabilities. • Collaboration with Data/ML Teams - Work closely with data scientists and ML engineers to provision scalable cloud hosting environments The candidate should also demonstrate a general understanding, 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 full stack software development team to ensure efficient, secure, and successful software deliveries of applications in multi-cloud environments. The candidate should exhibit experience with scalable cloud infrastructure, ML pipelines, deployment of microservices and APIs. Day to day responsibilities would include collaboration with the software and AI/ML engineering team, management of release schedules, software test and evaluation, and leading software compliance activities. The candidate will be working in a cross-functional team, and will contribute to the design, development and deployment of advanced applications in cloud and AI technology. Deployment environments include on-premises, commercial and government clouds. The candidate will work closely with technical and programmatic leadership to ensure deployments meet stakeholder needs and schedule constraints. Occasionally, customer facing demonstrations of software technology are required. Additional duties as assigned. Qualifications Required Skills • BS 8-10, MS 6-8, PhD 3-5 • Must be able to obtain/maintain Secret Clearance Technology and Tools The ideal candidate should demonstrate proficiency in the following technologies: • Software Engineering (Java, Python) • Expertise with infrastructure-as-code tools (Terraform, Ansible, CloudFormation) for controlled deployments • Proficiency in cloud security frameworks and compliance requirements (e.g., NIST, DoD STIGs) • AI/MLOps - (Azure AI Studio; AWS Sagemaker, Kubeflow, etc) • Familiarity with LLM APIs (OpenAI API, AWS Bedrock/boto) • 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 integrating software via RESTful APIs, Java APIs, WebSockets, Async Message Queues (Pub/Sub, etc) Preferred Technologies In addition, experience with the following is highly desirable: • Software application design and development using UML or SysML • Experience with modern LLM integration methods and applicable tools (LlamaIndex/LangChain) • 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. Arcfield ’s benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, Short Term and Long-Term Disability, Retirement and Savings, Learning and Development opportunities, wellness programs as well as other optional benefit elections. Min: $93,262.13 Max: $224,107.51 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. Apply tot his job