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Pavago

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

RemoteLATAMEastern Europe+Pakistan
Published
Role
Engineering Management
Experience
C-Level
Employment
Full-time
Company size
Startup
Salary not disclosed
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Open to Anywhere in LATAM & Eastern Europe + PK. Set where you work from to check your eligibility.

No BS summary

Highly technical, hands-on Head of Engineering needed for a fast-growing SaaS platform. Must have deep .NET/C# backend expertise, experience with distributed systems, AI/LLM infrastructure, and production code writing. Will lead a lean team, own architecture, infrastructure, reliability, and engineering standards, while remaining hands-on.

Core skills

.NETAI/LLMDistributed Systems

Required skills

C#ASP.NET CoreEntity Framework CoreMicroservicesClean ArchitectureDomain-Driven Design (DDD)MySQLRedisMongoDBLinuxCI/CDMonitoringLoggingAlertingObservabilityAPI architectureIntegrationRetry logicProvider failoverGraceful degradationFallback strategiesError handling

Optional skills

Startup experienceHigh-growth SaaS experienceScaling AI-powered SaaSAutomation platformsKubernetesDockerTerraformInfrastructure as Code

Required languages

English

What you'll do

  • 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 they require

  • 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.
  • 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.

Pavago is hiring for one of its clients seeking an Accounting & Finance Coordinator to support finance and operations teams.

🇺🇸 United StatesRecruitingStartup
Salary not disclosed