Physics-Informed Real-Time Optimization Architect

Airswift; United States; On-site; USD 150,000 - 210,000; Full time

Job summary

Airswift seeks a Computational Solutions Architect to design and deliver real-time optimization systems for industrial operations. You will translate complex engineering challenges into scalable AI-driven workflows using physics-informed models, CFD, and data-driven techniques.

You will collaborate with clients and ML engineers to define data flows, develop PoV pilots, and guide deployments from prototype to production. Strong communication and client-facing skills are essential.

Qualifications

• 5+ years designing or deploying computational systems in industrial or energy sectors.
• Strong foundation in physics-based simulation and numerical methods.
• Experience with real-time optimization and digital twins.

Responsibilities

• Lead technical design for client projects and translate challenges into workflows.
• Define data flows and integration requirements with ML engineers.
• Develop pilots and PoV initiatives to prove feasibility and value.
• Support production deployment and long-term adoption.
• Create reference architectures, templates, and documentation.
• Engage clients as trusted advisors with technical stakeholders.

Skills

Real-time optimization

Digital twins

Physics-based simulation

Machine learning

Client-facing communication

Education

MS/PhD in Engineering

MS/PhD in Applied Physics

MS/PhD in Computational Science

Job description

Airswift seeks a Computational Solutions Architect to design and deliver real-time optimization systems for industrial operations. You will translate complex engineering challenges into scalable AI-driven workflows using physics-informed models, CFD, and data-driven techniques.

You will collaborate with clients and ML engineers to define data flows, develop PoV pilots, and guide deployments from prototype to production. Strong communication and client-facing skills are essential.