Senior Backend Engineer - (.NET / AI Systems)
Pavago
Posted: March 12, 2026
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Quick Summary
We are hiring a Senior Backend Engineer to own the entire technical function of an early-stage SaaS platform. The ideal candidate will be responsible for writing production code, making architecture and infrastructure decisions, and guiding a small development team in a fast-moving startup.
Required Skills
Job Description
Job Title: Senior Backend Engineer (.NET / AI Systems)r
Position Type: Full-Time, Remote
Working Hours: U.S. Business Hours
About the Role
We are hiring a Senior Backend Engineer (.NET / AI Systems) to own the entire technical function of an early-stage SaaS platform. This is a hands-on leadership role where you will write production code daily while making architecture, infrastructure, and AI system decisions for a platform operating at scale.
You will be accountable for backend architecture, system reliability, AI pipelines, and guiding a small development team in a fast-moving startup environment.
Responsibilities
Backend Architecture & Engineering
• Design, build, and maintain a .NET 8.0 / C# backend using Clean Architecture and DDD principles
• Own the architecture and codebase across 14+ independently deployed microservices
• Deliver new features, refactor existing systems, and resolve performance bottlenecks
AI Systems & LLM Orchestration
• Design and operate production-grade AI pipelines across multiple LLM providers
• Optimize prompts and workflows for batch processing, personalization, and segmentation at scale
• Manage rate limits, failover strategies, and cost optimization across AI providers
Databases & Data Infrastructure
• Manage MySQL, Redis, and MongoDB in production environments
• Oversee bulk writes, caching strategies, event streams, and analytics pipelines
• Ensure data consistency and performance across distributed services
Infrastructure, Reliability & Monitoring
• Own Linux-based infrastructure, CI/CD pipelines, and service deployments
• Implement centralized logging, monitoring, alerting, and uptime tracking
• Proactively identify and mitigate reliability and scalability risks
API Integrations & System Resilience
• Manage 25+ third-party API integrations used in production
• Design retry, fallback, and graceful degradation strategies
• Ensure system stability when external providers fail or degrade
Team Leadership & Engineering Standards
• Lead and mentor a small engineering team through code reviews and architectural guidance
• Set and enforce engineering standards, workflows, and best practices
• Collaborate closely with the founder on product direction and technical strategy
What Makes You a Perfect Fit
• You are a senior, hands-on engineer who enjoys owning systems end-to-end
• You are comfortable being the most experienced technical person on the team
• You balance fast execution with long-term architectural thinking
• You take ownership of reliability, performance, and technical outcomes
• You thrive in early-stage startup environments
Required Experience & Skills
• Deep expertise in .NET 8.0, C#, ASP.NET Core, and Entity Framework Core
• Experience with distributed systems and independently deployed services
• Strong production experience with MySQL, Redis, and MongoDB
• Hands-on DevOps experience with Linux servers and CI/CD pipelines
• Experience managing large numbers of third-party API integrations
• Proven experience building and operating AI/LLM systems at scale
• Familiarity with AI-assisted development tools and workflows
• Strong understanding of monitoring, observability, and incident prevention
• Experience leading small engineering teams
• Strong English communication skills
What Does a Typical Day Look Like ?
• Write and review production backend code
• Make architectural decisions across services, databases, and AI pipelines
• Monitor system health and resolve reliability issues
• Guide developers through code reviews and technical feedback
• Collaborate with the founder on product and system evolution
In short: You own the technical foundation of the platform and ensure it scales reliably while enabling rapid product development.
Key Metrics for Success (KPIs)
• System uptime and service reliability
• Backend and AI system performance improvements
• AI cost efficiency and pipeline stability
• Code quality and deployment reliability
• Team execution and delivery quality
Interview Process
• Initial Screening Call
• Technical Interview with Pavago Recruiter
• Client Interview
• Offer & Onboarding