Senior Principal Software Engineer

Responsibilities

We are seeking a highly skilled Senior Full-Stack Software Engineer to join our team to build and scale our next-generation Intelligent Model-Based Systems Engineering (iMBSE) platform. In this role, you will be at the forefront of integrating state-of-the-art Artificial Intelligence into enterprise engineering workflows.

You will design and develop robust, cleanly separated system layers - from React-based user interfaces to scalable backend APIs powered by Python and Rust. A core focus of this position will be designing and implementing Agentic AI solutions, Custom Workflows, and RAG (Retrieval-Augmented Generation) services utilizing industry-leading LLMs like GPT-4o and Meta Llama 3.

You will work within a mature, automated DevSecOps environment, ensuring that code is secure, tested, and seamlessly deployed to Kubernetes clusters across AWS and Azure environments.

 

Key Responsibilities:

• Design, build, and maintain full-stack features across the iMBSE platform, including user-facing web applications, orchestration APIs, and backend microservices.
• Develop and deploy agentic AI solutions, such as LLM-driven workflows, RAG (Retrieval-Augmented Generation) services, and autonomous chat agents.
• Collaborate cross-functionally with product owners, domain experts, and other engineers to deliver extensible and secure solutions supporting MBSE workflows.
• Contribute to system architecture, ensuring well-defined interfaces, low coupling, and future extensibility.
• Ensure compliance with DevSecOps best practices, leveraging CI/CD pipelines and automated testing, security scanning, and cloud-native tooling (see “Our Tech Stack” below).
• Mentor junior engineers and champion engineering excellence through code reviews, design discussions, and knowledge sharing

Qualifications

Minimum Qualifications:

• BS 10-12, MS 8-10, PhD 5-7
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a closely related field.
• 5+ years of professional software engineering experience, including significant full-stack development.
• Extensive hands-on experience with Python and/or Rust in production environments.
• Proven track record building, deploying, and scaling agentic AI solutions (LLM agents, RAG pipelines, etc.) using frameworks such as LangChain, LlamaIndex, or similar.
• Proficiency with modern frontend technologies (React, Redux, JavaScript/TypeScript, HTML/CSS) and contemporary backend architectures (REST APIs, microservices).
• Strong understanding of cloud infrastructure and platforms (AWS, Azure, Kubernetes, Docker).
• Experience developing and maintaining CI/CD pipelines (GitLab, Docker, Maven), and automated testing frameworks (pytest, JUnit).
• Solid grasp of secure coding practices and DevSecOps workflows
• Ability to obtain/maintain Secret Clearance.

Preferred Qualifications:

• Experience integrating with engineering and MBSE tools (e.g., Cameo Systems Modeler, Teamwork Cloud).
• Familiarity with storage architectures (graph DBs, relational DBs, blob storage), API-driven platforms, and event-driven workflows.
• Experience with AI model orchestration (e.g., LLM/embedding model lifecycle, logging, compliance, RBAC).
• Knowledge of system observability tools (Prometheus, Grafana) and automated monitoring/alerting.
• Exposure to state-of-the-art LLMs (OpenAI GPT-4, Meta Llama 3, etc.) and related AI APIs

Technology and Tools

The ideal candidate should demonstration proficiency in the following technologies:

• Languages: Python, Rust, Java, JavaScript (React/Redux)
• Cloud/Infrastructure: AWS, Azure, Kubernetes, Docker, Terraform
• DevSecOps: GitLab, Maven, Semgrep, yGuard, OWASP
• Testing/Observability: pytest, JUnit, Jacoco, OTel, Grafana Stack, MLflow
• AI/ML: GPT models, Claude models, Embedding Models, LangChain, LlamaIndex, MCP
• MBSE/Domain: Cameo Systems Modeler, Teamwork Cloud, SysML v1 and v2

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: $127,584.65 Max: $251,035.08
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.