AI Systems Engineer (Aerospace Integrations) (Hub-Remote: DC or Philly Metro)
$156,500–$189,000 year
Remote · Philadelphia, Pennsylvania, United States or Alexandria, Virginia, United States
Job Summary
AI Systems Engineer (Aerospace Integrations) to design and build multi-agent AI pipelines that convert natural language mission requirements into validated spacecraft component designs. You will architect autonomous agentic workflows that orchestrate diverse AI techniques (LLMs, reinforcement learning, RAG, uncertainty quantification), integrate with engineering tools (CAD/FEA/ CAM), and deploy scalable cloud infrastructure. Responsibilities include translating physical constraints (mass, thermal envelopes, radiation shielding, vibro-acoustics) into prompt contexts and guardrails, designing automated CAE/FEA workflows, validating AI-generated designs with human-in-the-loop review, building cross-agent architectures (lead orchestrator coordinating specialized agents), converting natural language requirements to structured specifications (text → JSON), enabling tool integrations via APIs (MCP or equivalent), and ensuring secure, scalable deployments across cloud providers. The role emphasizes writing quality communication, remote collaboration, and aligning AI outputs with NASA/aerospace standards while supporting manufacturable hardware design. This is a full-time, salaried position with remote candidates encouraged (within 100 miles of Element 84’s Alexandria, VA or Philadelphia, PA hubs). Benefits include comprehensive healthcare, retirement plans, parental leave, flexible scheduling, PTO, and other family-friendly programs.
Required Qualifications
- 2+ years of experience as a software engineer within aerospace, defense, space, or similar manufacturing sectors
- Hands-on experience with CAD/CAE automation and scripting APIs (e.g., Python APIs for Autodesk Fusion 360, ANSYS, NASTRAN, or SolidWorks)
- Familiarity with aerospace-grade materials and design limits
- Ability to interpret and apply GD&T and NASA/aerospace engineering standards
- Strong Python skills; TypeScript is a plus
- API design, containerization, and connecting heterogeneous tools into automated pipelines
- Infrastructure as Code experience and reproducible cloud deployments
- Understanding of LLM fundamentals, prompt engineering, and structured outputs
- Experience building agentic architectures and multi-agent workflows
- Experience integrating AI with external engineering tools via APIs
- Cloud infrastructure deployment experience on AWS; familiarity with GCP/Azure is a plus
- Strong written communication and ability to translate requirements into structured specifications (text→JSON)
- Experience with evaluation frameworks for complex AI/LLM workflows
- Remote-friendly role with geographic constraints within the US (within 100 miles of Alexandria, VA or Philadelphia, PA)
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