[Hiring] AI Systems Engineer (Aerospace Integrations) @Element 84

Role Description

As an AI Systems Engineer, you will design and build the multi-agent systems that power NASA's Text-to-Spaceship initiative, an AI pipeline that converts natural language mission requirements into validated spacecraft component designs. Your goal is to turn science objectives into manufacturable hardware designs through reliable, AI-driven automation.

• Architect and build autonomous agentic workflows that orchestrate heterogeneous AI techniques (LLMs, reinforcement learning, RAG, uncertainty quantification).
• Build integrations with engineering tools (CAD, FEA, CAM).
• Deploy scalable infrastructure on AWS.
• Ensure the text-to-spaceship pipeline generates physically viable, safe, and manufacturable spacecraft components.
• Translate complex physics, NASA standards, and aerospace load cases into programmatic guardrails for multi-agent systems.

Key Responsibilities

• Physics-Informed AI Constraints: Translate physical constraints (mass, thermal envelopes, radiation shielding, vibro-acoustics) and mechanical properties into prompt contexts, structured outputs, and agent guardrails.
• Automated CAE & FEA Workflows: Design and implement programmatic workflows for Finite Element Analysis (FEA) and computational fluid dynamics (CFD).
• Domain Validation & Ground Truth: Serve as the human-in-the-loop expert to vet AI-generated structural designs.
• Multi-Agent Architecture: Design and implement agentic frameworks where a lead orchestrator agent coordinates specialized agents.
• Natural Language to Engineering Output: Build pipelines that convert natural language mission requirements into structured specifications.
• Tool Integration: Connect AI agents to external engineering tools via MCP and custom API integrations.
• Cloud Infrastructure: Deploy and scale AI workloads across cloud providers using containerized architectures.
• Evaluation & Observability: Build evaluation frameworks for agentic applications.

Qualifications

• 2+ years working as a software engineer within the aerospace, defense, space, or similar manufacturing sectors.
• Hands-on experience with the scripting APIs of industry-standard engineering tools.
• Familiarity with aerospace-grade materials and how their properties dictate design limits.
• Ability to interpret and programmatically apply GD&T and NASA/aerospace engineering standards.
• Experience with AWS services and architecture.
• Real-world experience with Python; secondary proficiency in TypeScript is a plus.
• Strong grasp of API design, containerization, and connecting heterogeneous tools and data formats into automated pipelines.
• Deep understanding of how large language models work.

Requirements

• Experience building agents with agentic libraries like Pydantic AI.
• Expertise in the Model Context Protocol (MCP) or equivalent approaches.
• Experience with ML techniques beyond LLMs applied to design optimization or engineering problems.
• Contributions to open-source AI libraries or a portfolio of deployed LLM applications.

Benefits

• Competitive medical, dental, and vision benefits.
• Life Insurance, Short & Long Term disability insurance.
• Voluntary Accident, Critical Illness & Hospital Insurance.
• 401(k) and Roth 401(k) retirement plans with a fixed 3% of salary employer contributions.
• Health savings account with a company contribution.
• Flexible spending accounts (medical, dependent care, and transportation).
• Company-paid parental leave after one year of employment.
• Flexible work schedules.
• Paid employee assistance program.
• 6 paid floating holidays.
• 4 weeks + 1 day paid Vacation Time Off per calendar year.
• 40 hours paid Sick Leave.
• Cell phone stipend.