Principal Software Engineer, FDE

Overview

In this Principal Software Engineer role, you will design and ship production-ready, reliable systems that turn ideas and data into scalable AI-powered solutions. You’ll work in cross-functional crews, embedding with customer teams to deliver outcomes within a Forward Deployed Engineering model. You’ll leverage AI and secure software practices to impact business strategy and customer success at scale. The opportunity emphasizes rapid delivery, collaboration, and continuous learning in a growth-minded culture.

Pay / Benefits

• health and wellness benefits
• financial future benefits
• flexible work environment
• inclusive culture
• competitive compensation
• benefits vary by country

Responsibilities

• Own end-to-end system design for cloud and AI workloads with balance of reliability, performance, cost, and maintainability
• Build, ship, and operate secure, production-ready solutions meeting enterprise standards
• Collaborate with stakeholders to translate business needs into measurable technical outcomes
• Lead delivery end-to-end across multiple workstreams and dependencies to improve reliability
• Drive customer success by delivering solutions that are adopted at scale and unblock delivery
• Create reusable assets, accelerators, and reference architectures for broader reuse
• Provide technical direction and mentorship across disciplines (product, data, security)
• Maintain clarity and momentum in ambiguous engagements while aligning with customer priorities
• Promote a culture of trust, accountability, and continuous improvement in line with company values
• Operate in a fast, feedback-driven environment using CI/CD, observability, and progressive delivery

Key requirements

• Bachelor’s Degree in Computer Science or related technical field or equivalent experience
• Experience partnering directly with customers or internal stakeholders to deliver end-to-end solutions
• Experience designing, deploying, and operating AI or LLM-based solutions including prompt engineering and model evaluation
• Familiarity with deploying and operating AI systems in production environments
• Experience using cloud AI platforms (Azure ML, OpenAI, or similar)
• Willingness to travel up to 25%

• collaboration across disciplines
• leadership and mentoring
• excellent communication
• AI/LLM development and deployment
• prompt engineering and retrieval-augmented techniques
• model evaluation, data quality, performance monitoring

…