Senior Software Engineer – FDE

Overview

In this role you will build reliable, production-ready systems and services as part of the Frontier Company Engineering team. You will partner with customers and cross-functional peers to translate business needs into scalable technical solutions, applying AI and modern engineering practices. You’ll own end-to-end architecture for cloud and AI workloads and drive outcomes that impact customer success at scale. This is a mission-driven, growth-focused role that emphasizes security, quality, and collaboration.

Responsibilities

• Put security first by building solutions that meet enterprise standards from design to production
• Translate business needs into technical solutions by partnering with stakeholders and defining success metrics
• Design and lead end-to-end architecture for cloud and AI workloads
• Deliver quickly using CI/CD, automated testing, observability, and progressive delivery
• Drive customer success by delivering production-ready solutions and enabling adoption at scale
• Build reusable, scalable assets like accelerators and reference architectures
• Operate effectively in ambiguity, continuously learning and bringing clarity to complex engagements
• Lead and mentor across disciplines, providing technical direction and collaboration with product, data, and security partners
• Coordinate multiple workstreams and raise the bar on reliability and operational excellence for production services
• Model inclusive, customer-obsessed leadership and represent the company professionally with external stakeholders

Key requirements

• Bachelor in Computer Science or related field AND 6+ years of technical engineering experience with coding in C/C++/C#/Java/JavaScript/Python OR equivalent experience
• Experience partnering directly with customers or internal stakeholders to deliver end-to-end solutions

• Collaborative mindset
• Leadership and mentorship
• Customer-obsessed mindset
• AI/LLM-based solution design and deployment (prompt engineering, retrieval-augmented approaches, model tuning)
• Experience with AI cloud platforms and production-scale AI systems
• CI/CD, automated testing, observability, progressive delivery

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