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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.
Job Responsibility
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
Requirements
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
Nice to have
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