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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 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 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 We’d love to hear from you. #HeadOfEngineering #DotNet #CSharp #ASPNetCore #AIEngineering #LLM #Microservices #DistributedSystems #SaaS #BackendEngineering #EngineeringLeadership #DevOps #RemoteEngineering #TechLeadership
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.