Director of Software Engineering - US Remote

Core Responsibilities

• Own the end-to-end technical architecture of the AI answering service, including voice pipeline design, LLM orchestration, API integration layers, and real-time telephony infrastructure.
• Define and enforce architectural patterns for AI system reliability, latency management, failure recovery, and scalability across production environments.
• Make build-vs-buy-vs-integrate decisions for new AI capabilities; evaluate third-party models, frameworks, and platforms with a critical engineering eye.
• Establish and maintain technical documentation standards across all AI components, ensuring accuracy is kept current as systems evolve.
• Actively participate in design reviews, code reviews, and technical spike work — especially for high-risk or high-complexity components.
• Led the implementation of core platform components where needed, including AI service integrations, orchestration logic, and platform APIs.
• Diagnose and resolve complex production issues including inference latency, integration regressions, and telephony quality problems.
• Prototype and validate new AI capabilities before committing to full implementation cycles.

Team Leadership & Development

• Build and lead a high-performing engineering team as headcount grows; initially operate as both a technical lead and individual contributor.
• Hire, onboard, and develop engineers with a focus on AI/ML fluency, software craftsmanship, and a bias toward continuous improvement.
• Foster a culture of psychological safety, technical rigor, and iterative delivery — where engineers learn from failure as readily as from success.
• Conduct regular 1:1s, provide candid performance feedback, and create individualized growth plans for direct reports.

External Partner & Vendor Management

• Serve as the primary engineering accountability owner for outsourced development partners as required; setting quality standards, reviewing deliverables, and managing the integration of external work into production systems.
• Evaluate third-party AI platforms, cloud services, and tooling; make and document vendor selection decisions.
• Ensure security, compliance, and data governance requirements are embedded into partner contracts and delivery expectations.

Engineering Operations & Delivery Excellence

• Define and track engineering KPIs: deployment frequency, system uptime, latency SLAs, error rates, and mean time to recovery.
• Lead the team's adoption of modern development practices including AI-augmented development workflows, automated testing for ML outputs, and continuous deployment pipelines.
• Owning the engineering budget and resource allocation; communicate tradeoffs clearly to the CTO.
• Collaborate with Product, Clinical, and Operations to translate requirements into reliable, scalable software — and to push back constructively when timelines or scope are unrealistic.

Cross-Functional & Strategic Contribution

• Partner with the Director of Product Management to align technical roadmap sequencing with product strategy and customer commitments.
• Represent engineering in executive conversations; translate technical realities into business risk and opportunity language.
• Contribute to PerfectServe's broader AI strategy, sharing perspectives on emerging capabilities, architectural evolution, and responsible AI practices.