Senior Backend Engineer

flexai; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

FlexAI seeks a Senior Backend Engineer (Infrastructure & AI Platform) to architect and build core backend systems powering its AI compute and PaaS platform. You will work at the intersection of distributed systems, cloud infrastructure, and AI platform engineering, enabling large-scale model training and orchestration.

Expect high ownership, autonomy, and contribution to an enterprise-grade platform. This role is ideal for engineers who enjoy deep-tech challenges beyond typical SaaS development.

Qualifications

• 8+ years of backend or infrastructure engineering experience.
• Expert-level proficiency in Golang (must-have).
• Strong experience building production-grade distributed systems.
• Proven track record working on infrastructure platforms, PaaS, or deep-tech systems.

Responsibilities

• 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.
• Collaborate with AI/ML and Runtime teams to integrate systems with training pipelines and inference infrastructure.

Skills

Golang

Distributed systems

Backend engineering

Platform engineering

Tools

Kubernetes

Docker

Cloud (AWS/GCP/Azure)

gRPC

PostgreSQL

Redis

Job description

About FlexAI

Build and Deploy AI the right way, anywhere.

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.

Founded by Brijesh Tripathi, who brings experience from Nvidia, Apple, Tesla, Intel and Zoox, FlexAI is not just building a product – we’re shaping the future of AI. Our teams are strategically distributed across Silicon Valley and Bengaluru, united by a shared mission: to deliver more compute with less complexity.

If you're passionate about shaping the future of artificial intelligence, driving innovation and contributing to a sustainable and inclusive AI ecosystem, FlexAI is the place for you !

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 environment — 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