Head of Engineering

Head of Engineering (.NET, AI/LLM & Distributed Systems) – Remote

Position Type: Full-Time, Remote
Working Hours: U.S. Business Hours
Location: Remote — Pakistan, LATAM & Eastern Europe Preferred

About the Role

We’re hiring a highly technical, hands-on Head of Engineering to own the engineering function for a fast-growing SaaS platform.

This is not a purely managerial role. You’ll remain deeply involved in production engineering while leading a lean technical team and owning architecture, infrastructure, reliability, and engineering standards.

You’ll work across:

• .NET / C# backend engineering

• Distributed systems and microservices

• AI & LLM infrastructure

• Databases and data pipelines

• DevOps, CI/CD and observability

• Third-party API integrations

• Engineering leadership and technical strategy

If you’re a senior engineering leader who still enjoys writing production code, solving difficult architecture problems, and owning systems end-to-end, this role is built for you.

What You’ll Own

Backend Engineering & Architecture

• Design, build, and maintain scalable backend systems using:

• .NET 8.0

• C#

• ASP.NET Core

• Entity Framework Core

• Own architecture across 14+ independently deployed microservices

• Apply Clean Architecture and Domain-Driven Design (DDD) principles

• Ship new product capabilities while improving existing systems

• Diagnose and resolve performance bottlenecks

• Improve scalability, maintainability, and engineering standards

• Make pragmatic architectural decisions that balance speed with long-term reliability

AI & LLM Systems

• Design and operate production-grade AI/LLM pipelines

• Manage workflows spanning multiple AI providers

• Build scalable AI capabilities for:

• Personalization

• Segmentation

• Automation

• AI-assisted product features

• Optimize:

• Prompting

• Orchestration

• Provider routing

• Failover logic

• Monitor and improve:

• Token usage

• Rate limits

• Latency

• Reliability

• AI infrastructure costs

• Introduce effective AI-assisted development workflows across engineering

Databases & Data Infrastructure

• Manage production environments using:

• MySQL

• Redis

• MongoDB

• Design and improve caching strategies

• Support analytics pipelines and event-driven workflows

• Manage high-volume and bulk data operations

• Optimize database schemas, indexing, and queries

• Maintain data consistency and performance across distributed services

Infrastructure, DevOps & Reliability

• Own Linux-based production infrastructure

• Maintain and improve CI/CD pipelines

• Oversee deployments and release reliability

• Implement centralized:

• Monitoring

• Logging

• Alerting

• Observability

• Identify infrastructure and scalability risks proactively

• Improve uptime, incident response, and deployment stability

• Strengthen engineering processes around production reliability

APIs, Integrations & Resilience

• Own 25+ production third-party API integrations

• Build resilient integration patterns including:

• Retry logic

• Provider failover

• Graceful degradation

• Fallback strategies

• Error handling

• Protect platform stability during third-party outages and degraded services

• Improve fault tolerance across external dependencies and distributed workflows

Engineering Leadership

• Lead and mentor a lean engineering team

• Conduct meaningful code reviews and architecture reviews

• Remain hands-on with production code

• Establish engineering standards for:

• Code quality

• Documentation

• Testing

• Deployment

• Architecture

• Guide developers through complex technical decisions

• Collaborate directly with founders and leadership on:

• Product roadmap

• Technical priorities

• Architecture

• Scalability

• Engineering investment

• Build a culture centered on ownership, execution, and engineering quality

What Makes You a Strong Fit

You’re a strong fit if you:

• Are an experienced engineering leader who still codes

• Have deep backend expertise in the Microsoft/.NET ecosystem

• Have designed and operated distributed production systems

• Understand how microservices behave under real-world scale and failure conditions

• Have hands-on experience building AI/LLM systems in production

• Can own infrastructure rather than treating DevOps as someone else’s responsibility

• Think proactively about reliability, scalability, and technical debt

• Can lead a small team without becoming disconnected from the codebase

• Communicate technical tradeoffs clearly to founders and business leadership

• Thrive in high-ownership startup environments

Required Experience & Skills

Core Engineering

• Deep expertise with .NET 8.0, C#, ASP.NET Core and Entity Framework Core

• Strong distributed systems and microservices architecture experience

• Production experience with MySQL, Redis and MongoDB

• Experience with event-driven and asynchronous systems

• Strong API architecture and integration experience

• Experience managing complex distributed workflows

AI Engineering

• Proven experience building and operating AI/LLM systems in production

• Experience integrating multiple AI/LLM providers

• Understanding of:

• Prompt orchestration

• Rate limits

• Failover

• Latency

• Cost optimization

• Production reliability

DevOps & Reliability

• Hands-on experience with:

• Linux infrastructure

• CI/CD

• Production deployments

• Monitoring

• Logging

• Observability

• Strong understanding of system scalability and reliability engineering

Leadership

• Experience leading and mentoring software engineers

• Strong code-review and architecture-review capabilities

• Ability to own technical priorities and engineering execution

• Excellent written and spoken English

• Ability to work closely with non-technical leadership

Nice to Have

• Startup or high-growth SaaS experience

• Experience scaling AI-powered SaaS or automation platforms

• Kubernetes

• Docker

• Terraform / Infrastructure as Code

• Event streaming and high-throughput architectures

• Advanced asynchronous processing experience

• AI inference and cost optimization experience

• Experience implementing AI-assisted engineering workflows

What a Typical Day Looks Like

Your day could include:

• Writing and reviewing production .NET/C# code

• Making architectural decisions across microservices

• Debugging a production performance or reliability issue

• Reviewing AI pipeline latency, cost, or provider performance

• Helping an engineer work through a complex implementation

• Reviewing database or caching performance

• Improving monitoring and deployment workflows

• Meeting with founders on product and engineering priorities

• Designing the architecture for an upcoming platform capability

In short: you own the technical foundation of the platform while keeping the engineering organization moving quickly and reliably.

Key Metrics for Success

• Platform uptime and system reliability

• Backend performance and scalability

• AI pipeline stability, latency, and cost efficiency

• Deployment success and engineering velocity

• Reduction in production incidents

• Code quality and technical debt management

• Reliability of third-party integrations

• Team delivery consistency

• Infrastructure stability and observability

Why This Role Stands Out

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True technical ownership of a growing SaaS platform

• Hands-on leadership rather than management-only work

• Direct influence over architecture and engineering strategy

• Production exposure to AI/LLM systems at scale

• Ownership across backend, infrastructure, data, integrations, and reliability

• Direct collaboration with founders and leadership

• Fully remote environment

• Opportunity to shape the engineering organization as the platform scales

Interview Process

• Initial Screening Call

• Technical Interview with Pavago Recruiter

• Technical & Architecture