Software Engineer - Cloud/AI Application Engineer

Roles and Responsibilities

The candidate should be capable to work 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
• Cloud and Information Technology - including cloud-based architecture, database architecture, and data sharing protocols
• Cloud Infrastructure Engineering - design, deployment and management of secure, scalable cloud architectures across AWS and Azure environments
• Configuration of networking, storage and compute resources to support data-intensive workloads
• The design and implementation of end-to-end AI solution, data services, and APIs into production applications
• Infrastructure-as-Code (IaC) using Terraform
• 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

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 implementation of secure, scalable cloud-based software and infrastructure to support AI/ML use cases. The candidate will contribute to the automation, containerization, and orchestration of AI workloads using modern DevOps and MLOps practices. The candidate will be working in a cross-functional team designing, developing and deploying advanced applications leveraging cloud-native services, data pipelines, and distributed computing architectures across platforms such as Azure and AWS. The role emphasizes compliance with industry network and security standards including NIST. Occasionally, customer facing demonstrations of software technology are required.

Required

• BS 8-10, MS 6-8, PhD 3-5
• Must be able to obtain/maintain Secret Clearance

Technology and Tools

The ideal candidate should demonstration proficiency in the following technologies:

• Software Engineering (Java, Python)
• Cloud-native technologies and development (Python/FastAPI, SQL, Redis)
• Cloud security frameworks and compliance requirements (e.g., NIST, DoD STIGs)
• Proficiency with infrastructure-as-code tools (Terraform, Ansible, CloudFormation) for controlled deployments.
• Performance Optimization (server-side rendering, code splitting, CSS modules)
• 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 implementing authentication/authorization and role-based access controls (RBAC)
• Command-line (CLI) Proficiency (Bash, PowerShell, etc)
• 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
• Systems Engineering processes, methods, and tools as applied to systems lifecycles
• Digital Engineering methodologies and tooling

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.