Principal Software Engineer, Breeze

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.

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