Head of Engineering

We are seeking a highly technical and hands-on Head of Engineering to lead the engineering function of a fast-growing SaaS platform. This role goes beyond management, requiring active involvement in production engineering, architecture, infrastructure, reliability, and engineering standards. You will work remotely, preferably from Pakistan, LATAM, or Eastern Europe, aligning with U.S. business hours. The ideal candidate is a senior engineering leader who enjoys writing production code, solving complex architectural challenges, and owning systems end-to-end.

Key Responsibilities

- Lead backend engineering and architecture by designing, building, and maintaining scalable systems using .NET 8.0, C#, ASP.NET Core, and Entity Framework Core.
- Own the architecture of 14+ independently deployed microservices, applying Clean Architecture and Domain-Driven Design principles.
- Develop and operate production-grade AI/LLM pipelines, managing workflows across multiple AI providers to build scalable AI capabilities including personalization, segmentation, automation, and AI-assisted features.
- Optimize AI systems for prompting, orchestration, provider routing, failover logic, token usage, rate limits, latency, reliability, and infrastructure costs.
- Manage databases and data infrastructure including MySQL, Redis, and MongoDB; design caching strategies, support analytics pipelines, and optimize database performance and consistency.
- Oversee Linux-based production infrastructure, maintain and improve CI/CD pipelines, and implement centralized monitoring, logging, alerting, and observability to ensure deployment reliability and uptime.
- Own 25+ third-party API integrations, building resilient patterns with retry logic, failover, graceful degradation, fallback strategies, and error handling to protect platform stability.
- Lead and mentor a lean engineering team, conduct code and architecture reviews, establish engineering standards for code quality, documentation, testing, deployment, and architecture.
- Collaborate closely with founders and leadership on product roadmap, technical priorities, scalability, and engineering investments while fostering a culture of ownership and execution.

Required Qualifications

- Extensive experience with .NET 8.0, C#, ASP.NET Core, and Entity Framework Core.
- Strong background in distributed systems and microservices architecture.
- Proven production experience with MySQL, Redis, and MongoDB.
- Expertise in event-driven and asynchronous systems.
- Solid API architecture and integration skills, including managing complex distributed workflows.
- Hands-on experience building and operating AI/LLM systems in production, including integration of multiple AI providers.
- Deep understanding of prompt orchestration, rate limits, failover, latency, cost optimization, and production reliability in AI systems.
- Practical knowledge of Linux infrastructure, CI/CD, production deployments, monitoring, logging, and observability.
- Demonstrated leadership in mentoring engineers, conducting code and architecture reviews, and owning technical priorities.
- Excellent communication skills with the ability to work closely with non-technical leadership.

Preferred Qualifications and Benefits

- Experience in startup or high-growth SaaS environments.
- Background in scaling AI-powered SaaS or automation platforms.
- Familiarity with Kubernetes, Docker, Terraform, and Infrastructure as Code.
- Knowledge of event streaming, high-throughput architectures, and advanced asynchronous processing.
- Experience with AI inference and cost optimization.
- Ability to implement AI-assisted engineering workflows.

This fully remote role offers true technical ownership of a growing SaaS platform, combining hands-on leadership with direct influence over architecture and engineering strategy. You will engage with AI/LLM systems at scale and collaborate directly with founders and leadership, shaping the engineering organization as the platform evolves.

Typical Day

Your daily activities may include writing and reviewing production .NET/C# code, making architectural decisions, debugging performance issues, reviewing AI pipeline metrics, mentoring engineers, optimizing database and caching performance, improving monitoring and deployment workflows, and aligning with founders on priorities.

Success Metrics

Success will be measured by platform uptime, system reliability, backend performance, AI pipeline stability and cost efficiency, deployment success, reduction in incidents, code quality, reliability of integrations, team delivery consistency, and infrastructure stability.

If you have deep expertise in .NET backend engineering, distributed systems, AI/LLM infrastructure, and enjoy remaining hands-on while leading a team, this opportunity is designed for you.