Staff Backend Engineer

FlexAI is looking for a Staff Backend Engineer (Infrastructure AI Platform) with deep Golang expertise to architect and build the core backend systems powering our next-generation AI compute and PaaS platform. This role sits at the intersection of distributed systems, cloud infrastructure, and AI platform engineering , focused on enabling large-scale model training, inference, and orchestration across heterogeneous compute architectures. As a Staff Engineer, you will operate as a technical leader driving backend architecture, scaling platform services, and building high-performance infrastructure components that power AI workloads in production environments. This is not a traditional backend role. You will be building platform-grade systems that support AI runtimes, scheduling, resource orchestration, and multi-tenant cloud infrastructure. What you'll Own Core Platform Infrastructure Backend Architect and develop high-performance backend services in Golang for FlexAI s AI PaaS and infrastructure platform Design backend systems that support distributed AI workloads, runtime orchestration, and platform automation Build internal platform APIs that power model deployment, job scheduling, and compute lifecycle management Develop backend components that interface with GPU/compute infrastructure and AI runtimes Distributed Systems Scalability Design and scale microservices and event-driven backend architectures for high-throughput AI workloads Optimize backend systems for low latency, high concurrency, and fault tolerance Implement robust service-to-service communication (gRPC/REST, message queues, async pipelines) Drive system reliability, observability, and resilience across platform services AI Platform Integration Collaborate with AI/ML and Runtime teams to integrate backend systems with: Model training pipelines Inference infrastructure Experimentation workflows Dataset and artifact management systems Enable seamless orchestration of AI workloads across cloud and on-prem environments Build backend abstractions that simplify AI infrastructure consumption for end users Cloud-Native Platform Engineering Work closely with DevOps/SRE teams on CI/CD, deployment automation, and infrastructure scalability Design backend services that are fully cloud-native and Kubernetes-native Contribute to platform architecture decisions around multi-region, multi-cloud infrastructure Improve system monitoring, logging, and performance diagnostics for platform services Technical Leadership Lead architecture reviews and set backend engineering standards for platform services Mentor senior engineers and guide complex technical problem-solving Drive long-term technical roadmap for backend infrastructure and AI platform capabilities Partner with Product, Runtime, and Infra leadership to translate deep-tech requirements into scalable backend systems Required Qualifications Core Engineering Experience 8 12+ years of backend or infrastructure engineering experience Expert-level proficiency in Golang (must-have, heavy hands-on) Strong experience building production-grade distributed systems Proven track record working on infrastructure platforms, PaaS, or deep-tech systems Infrastructure Systems Knowledge Deep understanding of cloud-native architectures and containerized environments Strong experience with Kubernetes, Docker, and cluster orchestration systems Experience designing backend systems for high-scale, multi-tenant platforms Familiarity with compute scheduling, resource management, or platform runtimes is a strong plus Databases Data Systems Experience with scalable distributed databases (PostgreSQL, Cassandra, DynamoDB, etc.) Strong understanding of caching layers, queues, and streaming systems (Redis, Kafka, etc.) Expertise in designing data models for high-throughput backend platforms AI / Platform Exposure (Highly Preferred) Experience working on AI/ML platforms, model infrastructure, or data platforms Familiarity with ML pipelines, inference systems, or GPU-backed workloads Exposure to frameworks like PyTorch, TensorFlow infrastructure, or model serving systems is a plus Tech Stack (Indicative) Languages: Golang (Primary), Python (Secondary) Infrastructure: Kubernetes, Docker, Cloud (AWS/GCP/Azure) Architecture: Microservices, gRPC, Event-driven systems Data: SQL + NoSQL databases, caching, streaming systems Observability: Prometheus, Grafana, OpenTelemetry (or similar) What Makes This Role Unique at FlexAI Build backend systems powering next-gen AI compute infrastructure (not SaaS CRUD apps) Work on deeply technical problems across AI runtime, orchestration, and distributed infrastructure Direct influence on architecture as the platform scales from Beta to enterprise-grade deployment High ownership and technical autonomy in a research-driven, deep-tech environment Ideal Candidate Profile (Who Will Thrive Here) Infra-first backend engineers (not just API developers) Engineers from companies building: AI infra, cloud platforms, developer platforms, or deep-tech systems Strong systems thinkers who enjoy low-level performance, scalability, and architecture challenges Startup-minded builders comfortable operating in ambiguous, high-ownership environments