Principal Software Engineer, Breeze

Job description

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Software Engineer, Breeze based in United States.** This is a high-impact technical leadership role at the intersection of distributed systems, generative AI, and customer-facing product innovation. You will serve as the technical anchor for a large-scale AI assistant and help define the architecture and roadmap for its next stage of evolution. The role combines hands-on engineering with platform thinking, enabling teams to build sophisticated AI-powered experiences and workflows. You will work with massive data volumes and millions of users while designing systems that balance reliability, cost, speed, and trust. Your work will shape how AI agents interact with CRM data, internal tools, and third-party ecosystems. You will also influence engineering practices through mentorship, technical leadership, and reusable platform primitives. This is an opportunity to build production-grade AI systems with a direct connection to measurable customer outcomes. ### Accountabilities - Define scalable architecture and technical patterns for AI agents interacting safely with CRM data, agentic tools, memory, scheduled prompts, and third-party ecosystems. - Establish the right balance between deterministic and non-deterministic workflows, optimizing for reliability, cost, trust, and outcome quality. - Extend the AI platform to support new artifact types, internal builders, and high-value customer workflows across the broader product ecosystem. - Partner with context and data-focused teams to ensure AI experiences are powered by complete, accurate, and actionable customer information. - Rapidly prototype and validate emerging generative AI capabilities, including LLMs, RAG, and agentic frameworks, while determining when solutions are ready for production. - Write and ship production-quality code while leading high-impact initiatives from early prototypes through reliable systems operating at scale. - Establish strategies for AI evaluation, observability, privacy, guardrails, and reliability so customers can confidently use AI for meaningful business processes. - Collaborate with Product, AI Research, Engineering, and Ecosystem teams to make internal tools and APIs accessible through the AI platform. - Develop reusable platform primitives such as skills, tools, APIs, and agentic infrastructure that other teams can build upon. - Mentor senior engineers and raise organizational fluency in prompt engineering, model selection, agentic architectures, and production AI systems. - Advocate for customer needs and ensure technical decisions translate into valuable experiences for sales and marketing professionals. - Drive technical direction in an ambiguous, rapidly changing environment while maintaining a strong bias toward action and measurable outcomes. ## Requirements - Proven experience designing and scaling high-throughput, low-latency distributed systems with demanding reliability and concurrency requirements. - Deep hands-on experience with generative AI technologies, including LLM orchestration, vector databases, RAG pipelines, and multi-agent frameworks. - Strong understanding of model architecture trade-offs, fine-tuning approaches, inference costs, and practical considerations for deploying AI at scale. - Demonstrated experience designing autonomous or semi-autonomous systems involving tool calling, complex state management, action execution, and graceful failure recovery. - Strong platform-engineering mindset, with experience building reusable primitives, APIs, tools, or frameworks for other engineering teams and partners. - Track record of delivering customer-focused products and balancing technical decisions with user experience and business outcomes. - Ability to turn ambiguous problems into clear plans, working prototypes, and production-ready software without excessive process overhead. - Curiosity and adaptability in a rapidly evolving AI landscape, with the ability to evaluate new models, research, and frameworks critically. - Strong communication and technical leadership skills, with the ability to influence cross-functional stakeholders and mentor experienced engineers. - Willingness to work hands-on while also shaping long-term architecture, engineering standards, and platform strategy. - Experience working with AI systems where reliability, privacy, evaluation, observability, and trust are critical. - Proficient written and spoken English and professional experience with an object-oriented programming language. - Ability to travel as required, including participation in regional in-person onboarding and team events. ## Benefits - Annual cash compensation range of **$266,200–$425,900 USD**, with individualized packages based on skills, experience, qualifications, and other job-related factors. - Potential eligibility for equity compensation through restricted stock units (RSUs), depending on the role and compensation package. - Flexible work options with a remote-friendly environment and opportunities to build strong connections with colleagues. - Regional in-person onboarding for engineering employees, plus additional opportunities for team and product gatherings. - Comprehensive benefits and perks designed to support employees' professional and personal well-being. - Opportunities to work on large-scale AI products with significant customer impact. - A culture centered on customer focus, bold thinking, rapid learning, adaptability, ownership, and meaningful results. - An environment that emphasizes trust, flexibility, clarity, and high-quality work rather than traditional office presence. - Support for workplace accommodations during the recruitment and employment process.