Role Overview

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.

As a Senior Backend Engineer, you'll drive backend architecture, scale platform services, and build high-performance infrastructure components that power AI workloads in production environments — influencing how the platform evolves from Beta to enterprise-grade deployment. Expect high ownership and technical autonomy in a research-driven, deep-tech setting — not SaaS CRUD apps.

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

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 Experience:

- 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

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

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

📌 Senior Backend Engineer (Bengaluru)
🏢 FlexAI
📍 Bengaluru