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Senior Backend Engineer
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À propos
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 !
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
The pay range for this role is:
180,000 - 225,000 USD per year (US)
Compétences linguistiques
- English
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