Senior Backend Engineer

What You'll Do

Core Platform & Infrastructure Backend

• 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

Distributed Systems & Scalability

• 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

AI Platform Integration

• 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

Cloud-Native & Platform Engineering

• 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

Technical Leadership

• 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

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 You'll Need to Be Successful

Core Engineering

• 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

Infrastructure & 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

Databases & Data Systems

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

AI / Platform Exposure (Highly Preferred)

• 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