Senior Principal Software Engineer

Arcfield; Home Creek (VA); On-site; USD 127,584 - 251,035; Full time

Benefits offered by this job

Health insurance

Paid time off

Retirement and savings plans

Job summary

Arcfield is seeking a highly skilled Senior Full‑Stack Software Engineer to enhance its Intelligent Model‑Based Systems Engineering platform. The role involves designing robust user interfaces and backend APIs, focusing on AI integration using industry-leading models like GPT‑4 and Meta Llama 3.

Successful candidates will have a strong background in software engineering with at least 5 years of experience, with a focus on Python and Rust, a solid understanding of cloud environments, and a commitment to DevSecOps practices.

Qualifications

• 5+ years of professional software engineering experience in full-stack development.
• Extensive experience with Python and/or Rust in production environments.
• Ability to obtain/maintain Secret Clearance.

Responsibilities

• Design, build, and maintain full‑stack features across the iMBSE platform.
• Develop and deploy AI solutions like LLM‑driven workflows and RAG services.
• Mentor junior engineers and lead code reviews.

Skills

Python

Rust

JavaScript (React)

Cloud infrastructure (AWS, Azure)

DevSecOps

CI/CD pipelines

Education

Bachelor’s or Master’s degree in Computer Science or Engineering

Tools

GitLab

Kubernetes

Docker

Job description

Responsibilities

We are seeking a highly skilled Senior Full‑Stack Software Engineer to join our team to build and scale our next‑gen 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 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.
• 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 demonstrate 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.

Compensation and Benefits

Equal Pay Act: This is the projected compensation range for this position. Min: $127,584.65; Max: $251,035.08.

This role is a federal government contractor. Arcfield invests in its employees beyond just compensation. Benefits 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, and other optional benefit elections.

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.