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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
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
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 Interview with Client
Final Leadership Interview
Offer & Onboarding
What Happens After You Apply
Right after you apply, you’ll receive an email invitation from Spark Hire to record your Intro Video. It’s a short, self-recorded video completed on your own time and is the final step needed to complete your application.
Instead of repeating your background across multiple screening calls, you get to introduce yourself once and give the hiring team a better sense of your experience and communication before the first interview.
Don’t overthink it. You can record your responses multiple times, and discarded takes are not shared.
Please check both your inbox and spam folder for the Spark Hire invitation.
Apply Now
If you:
Have deep .NET/C# backend engineering expertise
Have built and scaled distributed systems and microservices
Have real production experience with AI/LLM infrastructure
Enjoy remaining hands-on while leading engineers
Want end-to-end ownership of a growing SaaS platform