Principal Engineer

About Showpad
Showpad is a leading sales enablement platform purpose-built for modern, distributed sales organizations. Our product strategy is deeply invested in Generative AI to transform sales readiness, content lifecycle management, seller recommendations, and agentic workflows that materially improve sales productivity and effectiveness at scale.
As we accelerate our AI roadmap, we are hiring a Principal AI Engineer to lead the design, development, and delivery of next-generation AI capabilities while mentoring and scaling a high-potential team of junior AI and ML engineers.
The Role
The Principal AI Engineer will be a hands-on technical leader responsible for architecting, building, and shipping AI-powered product capabilities that directly impact customer outcomes and revenue. This role combines deep technical expertise in modern AI systems with people leadership, technical mentorship, and cross-geo collaboration.
You will set technical direction, establish engineering best practices, and serve as the escalation point for complex AI design decisionswhile remaining close to production code and real customer use cases.
Key Responsibilities
Technical Leadership & Architecture

• Design, build, and scale production-grade AI and Generative AI systems for sales enablement use cases including:
• Sales readiness and coaching
• Content and library lifecycle intelligence
• Personalized seller recommendations
• Agentic and workflow-driven productivity solutions
• Architect and evolve systems using:
• Large Language Models (LLMs)
• Agent frameworks and orchestration patterns
• Model Context Protocol (MCP) servers
• Agent-to-Agent (A2A) communication protocols
• Retrieval-augmented generation (RAG), embeddings, vector search, and hybrid pipelines
• Make informed trade-offs between build vs. buy, open-source vs. commercial models, latency vs. cost, and accuracy vs. explainability.
  

Hands-On Development

• Write, review, and maintain high-quality production code across AI/ML services.
• Own model evaluation, prompt and agent design, observability, and continuous improvement loops.
• Drive responsible AI practices including data governance, bias mitigation, security, and compliance.
  

Team Leadership & Mentorship

• Lead and mentor a team of relatively junior AI and ML engineers, raising their technical bar and accelerating their growth.
• Challenge assumptions, inspire curiosity, and instill a culture of engineering excellence, experimentation, and accountability.
• Establish coding standards, design review practices, and learning pathways for AI engineers.
  

Product Impact & Delivery

• Partner closely with Product, Design, and Customer teams to translate business problems into scalable AI solutions.
• Maintain a strong bias toward shippingdelivering measurable customer and business impact, not just prototypes.
• Influence roadmap decisions with technical insight and data-driven recommendations.
  

Global Collaboration

• Work effectively across time zones with teams in Europe, North America, and Australia.
• Balance responsiveness with sustainable work practices, modeling healthy collaboration and personal well-being in a global environment.
  

Required Qualifications
Experience & Expertise

• 5+ years of hands-on experience building and deploying AI, Generative AI, and ML applications in production.
• Deep, current knowledge of:
• LLM architectures and ecosystems
• Prompt engineering, fine-tuning, and evaluation techniques
• Agent frameworks, orchestration patterns, MCP servers, and A2A protocols
• Proven experience delivering AI-powered products that have made a real, measurable impact in the last few years.
  

Engineering Excellence

• Strong software engineering fundamentals (APIs, distributed systems, data pipelines, cloud-native architectures).
• Experience with model monitoring, performance optimization, and cost control at scale.
• Ability to reason clearly about system design under real-world constraints.
  

Leadership & Communication

• Demonstrated ability to lead, mentor, and elevate junior engineers.
• Clear, confident communicator who can explain complex AI concepts to technical and non-technical stakeholders.
• Comfortable influencing without authority in a matrixed, global organization.
  

Nice to Have

• Experience in B2B SaaS, sales enablement, revenue intelligence, or productivity platforms.
• Exposure to multi-tenant AI systems and enterprise-grade security/compliance requirements.
• Experience scaling AI capabilities from early adoption to broad customer usage.