
Head of Engineering
Position Type: Full-Time, Remote Working Hours: U.S. Business Hours Location: Remote (Pakistan, LATAM, Eastern Europe Preferred)
About the Role
We are hiring a highly technical and hands-on Head of Engineering to own the entire engineering function of a fast-growing SaaS platform. This role combines deep backend engineering, distributed systems architecture, AI infrastructure, and technical leadership in a fast-moving startup environment.
This is not a purely managerial role. You will actively write production code, make architectural decisions, oversee infrastructure reliability, and guide a lean engineering team while helping scale a platform operating across multiple services and AI-powered workflows.
The ideal candidate thrives in startup environments, takes ownership of systems end-to-end, and understands how to balance rapid product development with long-term scalability and reliability.
What You’ll Own
Backend Architecture & Engineering
AI Systems & LLM Infrastructure
Databases & Data Infrastructure
Infrastructure, DevOps & Reliability
API Integrations & System Resilience
Team Leadership & Engineering Standards
What Makes You a Great Fit
Required Experience & Skills
• Strong English communication skills
Preferred Experience
Startup or high-growth SaaS experience
Experience scaling AI-powered platforms or automation systems • Familiarity with Kubernetes, Docker, Terraform, or infrastructure-as-code tooling • Experience optimizing AI cost efficiency and inference performance • Knowledge of event streaming, asynchronous processing, and high-throughput architectures • Familiarity with AI-assisted software development workflows
What a Typical Day Looks Like
A Head of Engineering’s day revolves around balancing architecture, execution, reliability, and leadership. You will:
• Write and review production backend code • Make architectural decisions across services, infrastructure, and AI systems • Monitor production systems and resolve scalability or reliability issues • Guide developers through code reviews and technical implementation decisions • Collaborate with leadership on roadmap planning and technical prioritization • Improve deployment reliability, observability, and engineering workflows • Optimize AI systems for performance, stability, and cost efficiency
In essence: you own the technical foundation of the platform and ensure the engineering organization can scale reliably while moving quickly.
Key Metrics for Success (KPIs)
System uptime and platform reliability
AI pipeline stability and operational efficiency • Deployment reliability and engineering velocity • Backend performance and scalability improvements • Code quality and reduction in technical debt • Team delivery consistency and engineering execution quality • Infrastructure stability and incident reduction
Interview Process
Initial Screening Call
Technical Interview with Pavago Recruiter • Technical / Architecture Interview with Client • Final Leadership Interview
• Offer & Onboarding
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