FlexAI

Senior Backend Engineer

Santa Clara, CA San Jose, CA
Golang Python Kubernetes Docker AWS GCP Azure Microservices gRPC SQL PostgreSQL Cassandra DynamoDB Redis Kafka Prometheus Grafana OpenTelemetry TensorFlow PyTorch
Description

Senior Backend Engineer

Location: Santa Clara, CA

Department: Engine

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.


This position is In-Person and located at our San Jose, CA Office.


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

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

About the Company

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 bring 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 !

FlexAI
FlexAI

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