Founding Staff Product Engineer — 0→1 & Scale (Remote)

Pragmatike; Sacramento (CA); Remote; USD 200,000 - 400,000; Full time

Job summary

Pragmatike is recruiting on behalf of a fast-growing technology company building critical infrastructure that powers real-time business operations. We are seeking a Staff Founding Product Engineer to lead the development of important new products and capabilities within a rapidly scaling organization.

You will partner with customers and Product leadership to design and implement full-stack architectures, establish technical foundations, and translate ambiguous problems into scalable solutions,

Qualifications

• 7+ years of software engineering experience.
• Strong full-stack and product engineering experience.
• Proven 0→1 product development track record.
• Excellent product judgment and technical depth.
• Strong architecture and system design skills.
• Ability to work independently in highly ambiguous environments.

Responsibilities

• Lead 0→1 product initiatives from discovery through scale.
• Partner directly with customers and Product leadership.
• Design and implement full-stack product architectures.
• Establish technical foundations for new products.
• Translate ambiguous product problems into scalable solutions.
• Balance speed, product quality, and technical sustainability.
• Mentor engineers working on product initiatives.
• Influence product roadmap and engineering priorities.

Skills

7+ years experience

Full-stack engineering

0→1 product dev

Architecture & design

Product judgment

Independent worker

Customer collaboration

Job description

Pragmatike is recruiting on behalf of a fast-growing technology company building critical infrastructure that powers real-time business operations. We are seeking a Staff Founding Product Engineer to lead the development of important new products and capabilities within a rapidly scaling organization.

You will partner with customers and Product leadership to design and implement full-stack architectures, establish technical foundations, and translate ambiguous problems into scalable solutions,