Senior Backend Engineer

About FlexAI

The FlexAI Compute Infrastructure Platform provides an "end-to-end AI compute layer" for running and managing workloads across any cloud, any GPU, and any deployment model (public, hybrid, or on-prem). It brings together "1-click simplicity" for users with "enterprise-grade orchestration, security, and automation" under the hood.

FlexAI is looking for a Senior 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 — enabling large-scale model training, inference, and orchestration across heterogeneous compute. 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.

• →Architect and develop high-performance Golang services for FlexAI's AI PaaS and infrastructure platform
• →Build internal APIs powering model deployment, job scheduling, and compute lifecycle management
• →Develop components interfacing with GPU/compute infrastructure and AI runtimes

• Design and scale microservices and event-driven systems for high-throughput AI workloads
• Optimize for low latency, high concurrency, and fault tolerance
• Implement service-to-service communication (gRPC/REST, message queues, async pipelines)
• Drive reliability, observability, and resilience across services

• Collaborate with AI/ML and Runtime teams to integrate systems with training pipelines, inference infrastructure, experimentation workflows, and dataset/artifact management
• Enable orchestration across cloud and on-prem environments
• Build abstractions that simplify AI infrastructure consumption

• Design cloud-native, Kubernetes-native services
• Work with DevOps/SRE on CI/CD, deployment automation, and scalability
• Contribute to architecture decisions for multi-region, multi-cloud infrastructure
• Improve monitoring, logging, and diagnostics

• Lead architecture reviews and set engineering standards
• Mentor engineers and guide complex problem-solving
• Drive long-term roadmap for backend infrastructure and AI platform capabilities
• Partner with Product, Runtime, and Infra leadership to translate requirements into scalable systems 

• 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)

• 5+ 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 on infrastructure platforms, PaaS, or deep-tech systems

• Deep understanding of cloud-native architectures and containerized environments
• Strong experience with Kubernetes, Docker, and cluster orchestration
• Familiarity with compute scheduling, resource management, or platform runtimes is a strong plus

• Experience with distributed databases (PostgreSQL, Cassandra, DynamoDB, etc.)
• Strong understanding of caching, queues, and streaming systems (Redis, Kafka, etc.)

• Experience on AI/ML platforms, model infrastructure, or data platforms
• Familiarity with ML pipelines, inference systems, or GPU-backed workloads
• Exposure to PyTorch, TensorFlow infrastructure, or model serving systems is a plus

Ideal Candidate Profile (Who Will Thrive Here)

• Infra-first backend engineers (not just API developers)
• Background in 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 in ambiguous, high-ownership environments

What We Offer

• Competitive salary and benefits package
• Work on cutting-edge AI infrastructure
• Build products used by developers and enterprises
• High ownership, fast execution, real impact
• Collaborative, high-caliber team