Responsibilities

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.

Qualifications

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

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.

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Software Engineer - Cloud/AI Application Engineer