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Design and build scalable backend systems for observability, architecture modeling, and AI-driven recommendations using data pipelines, microservices, and system modeling. Integrate LLM and multi-agent capabilities, build architecture-pattern visibility services, and implement monitoring and resilient workflows while collaborating across product, AI, and engineering teams.
This is a high-impact individual contributor role on the engineering team of an early-stage AI/ML platform company focused on cloud-native architecture intelligence. You will design and build the intelligent backend systems that power observability, architecture modeling, and AI-driven recommendation engines, sitting at the intersection of distributed systems, data pipelines, and ML infrastructure.
Design and build scalable backend systems powering observability, architecture modeling, and recommendation engines using data pipelines, microservices, and system modeling techniques.
Collaborate with AI engineers to embed LLM-based and multi-agent intelligence within the platform, enabling rich recommendations and generative planning features.
Build services that identify architecture patterns and deliver actionable visibility to users.
Implement monitoring, fault-tolerant workflows, and observability layers for mission-critical services.
Work cross-functionally with product managers, AI researchers, and technical leadership to translate requirements into robust platform capabilities.
Share learnings and contribute to a strong, collaborative engineering culture.
4+ years of backend engineering experience at top-tier startups or technology companies, building production-grade systems.
Proven track record building scalable, distributed systems and microservices architectures, ideally in 0-to-1 product environments.
Expertise in Go or Python with a commitment to clean, idiomatic, maintainable code.
Hands-on experience with data pipelines, observability systems, and monitoring infrastructure for production services.
Deep knowledge of DevOps tooling, infrastructure-as-code, and cloud-native technologies.
Experience integrating or building with LLM-based systems, AI workflows, or multi-agent architectures.
Strong aptitude for performance tuning, debugging complex systems, and technical architecture design.
Prior startup experience and comfort operating with autonomy and ownership in fast-moving environments.
Practical experience with fault-tolerant workflow design and resilience patterns in mission-critical services.
Proficiency with AI-assisted development tools (such as Cursor or similar).
Strong Computer Science fundamentals; graduate-level education is a plus.
Domain experience with cloud architecture, infrastructure optimization, or technology stack modernization is a bonus.
Salary: $160,000 to $200,000 per year (USD)
Visa sponsorship: Not available
Fully remote, open to candidates based in the United States.
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