2 часа назад
Senior Principal Software Engineer (AI)
127 585 - 251 035$
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Senior Principal Software Engineer (AI/Full Stack): Building and scaling an intelligent model-based systems engineering platform with an accent on React interfaces, Python and Rust backend APIs, and agentic AI services. Focus on implementing LLM-driven workflows, RAG pipelines, Kubernetes deployment across AWS and Azure, and secure DevSecOps automation.
Location: Remote work allowed 100%; Home, Virginia
Salary: $127,584.65–$251,035.08 annually
Company
is a federal government contractor developing engineering and software solutions.
What you will do
- Build and scale full-stack features for an intelligent model-based systems engineering platform, including React applications, orchestration APIs, and backend microservices.
- Develop and deploy agentic AI solutions, LLM-driven workflows, RAG services, and autonomous chat agents.
- Collaborate with product owners, domain experts, and engineers to deliver secure and extensible MBSE solutions.
- Contribute to system architecture through well-defined interfaces, low coupling, and scalable design.
- Implement DevSecOps practices, CI/CD pipelines, automated testing, security scanning, and cloud-native deployments.
- Mentor junior engineers and promote engineering excellence through reviews, design discussions, and knowledge sharing.
Requirements
- 5+ years of professional software engineering experience, including significant full-stack development.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Production experience with Python and/or Rust, modern frontend technologies, REST APIs, and microservices.
- Experience building and scaling agentic AI solutions, LLM agents, and RAG pipelines using LangChain, LlamaIndex, or similar frameworks.
- Experience with AWS, Azure, Kubernetes, Docker, CI/CD, automated testing, and secure coding practices.
- Ability to obtain and maintain Secret Clearance.
Nice to have
- Experience with MBSE tools such as Cameo Systems Modeler and Teamwork Cloud.
- Knowledge of graph, relational, and blob storage architectures, event-driven workflows, and API-driven platforms.
- Experience with AI model orchestration, observability, monitoring, and alerting.
- Familiarity with GPT models, Meta Llama, Claude, embedding models, MCP, SysML, Prometheus, Grafana, and MLflow.
Culture & Benefits
- Health, life, disability, retirement, and savings benefits may be available depending on the position.
- Paid time off and holiday pay.
- Learning and development opportunities and wellness programs.
- Automated, mature DevSecOps environment supporting cloud-native engineering.
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