Senior Backend Engineer

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)

8+ 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

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

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